Introduction

For one of my machine learning classes we had a project that consumed financial data. I have extended that project to use machine learning to see if an indicator, or predictor, can be found that identifies market tops that occur prior to recessions. Then I use the model to build a trading strategy and backtest it to see how it performs.

Get Economic and Financial Data

Acquiring the data consists of two steps. First the code pulls the data into zoo objects which are then collapsed into a single data frame (df.data). Features are extracted from these series and added to the df.data data frame.

Sample call to pull economic data

Data is pulled from several sources include FRED, yahoo, and Google. The code below shows an example that pulls in the consumer price index (CPI) from the FRED. I pull data using quantmod, Quandl, and some manual extractions stored in spreadsheets.

# Consumer Price Index for All Urban Consumers: All Items
if (bRefresh == TRUE) {
  getSymbols("CPIAUCSL", src = "FRED", auto.assign = TRUE)
}
## [1] "CPIAUCSL"
## [1] "CPIAUCSL"
## [1] "USREC"
## [1] "UNRATE"
## [1] "PCEPI"
## [1] "CCSA"
## [1] "CCNSA"
## [1] "NPPTTL"
## [1] "U6RATE"
## [1] "PAYNSA"
## [1] "TABSHNO"
## [1] "HNONWPDPI"
## [1] "INDPRO"
## [1] "RRSFS"
## [1] "RSALES"
## [1] "W875RX1"
## [1] "RPI"
## [1] "PCOPPUSDM"
## [1] "NOBL"
## [1] "SCHD"
## [1] "PFF"
## [1] "HPI"
## [1] "GSFTX"
## [1] "LFMIX"
## [1] "LFMCX"
## [1] "LFMAX"
## [1] "LCSIX"
## [1] "BSV"
## [1] "VBIRX"
## [1] "BIV"
## [1] "VFSUX"
## [1] "LTUIX"
## [1] "PTTPX"
## [1] "NERYX"
## [1] "STIGX"
## [1] "HLGAX"
## [1] "FTRGX"
## [1] "THIIX"
## [1] "PTTRX"
## [1] "BFIGX"
## [1] "VTWO"
## [1] "EIFAX"
## [1] "ASDAX"
## Warning: ASDAX contains missing values. Some functions will not work if objects
## contain missing values in the middle of the series. Consider using na.omit(),
## na.approx(), na.fill(), etc to remove or replace them.
## [1] "TRBUX"
## [1] "PRVIX"
## [1] "PRWCX"
## [1] "ADOZX"
## [1] "MERFX"
## [1] "CMNIX"
## [1] "CIHEX"
## [1] "IMPCH"
## [1] "EXPCH"
## [1] "IMPMX"
## [1] "EXPMX"
## [1] "HSN1FNSA"
## [1] "HNFSUSNSA"
## [1] "BUSLOANS"
## [1] "TOTCI"
## [1] "BUSLOANSNSA"
## [1] "REALLNNSA"
## [1] "REALLN"
## [1] "RELACBW027NBOG"
## [1] "RELACBW027SBOG"
## [1] "RREACBM027NBOG"
## [1] "RREACBM027SBOG"
## [1] "RREACBW027SBOG"
## [1] "RREACBW027NBOG"
## [1] "MORTGAGE30US"
## [1] "CONSUMERNSA"
## [1] "TOTLLNSA"
## [1] "DPSACBW027SBOG"
## [1] "DRCLACBS"
## [1] "TOTCINSA"
## [1] "SRPSABSNNCB"
## [1] "ASTLL"
## [1] "FBDILNECA"
## [1] "ASOLAL"
## [1] "ASTMA"
## [1] "ASHMA"
## [1] "ASMRMA"
## [1] "ASCMA"
## [1] "ASFMA"
## [1] "CCLBSHNO"
## [1] "FBDSILQ027S"
## [1] "FBLL"
## [1] "NCBDBIQ027S"
## [1] "DGS10"
## [1] "^TNX"
## Warning: ^TNX contains missing values. Some functions will not work if objects
## contain missing values in the middle of the series. Consider using na.omit(),
## na.approx(), na.fill(), etc to remove or replace them.
## Warning: CL=F contains missing values. Some functions will not work if objects
## contain missing values in the middle of the series. Consider using na.omit(),
## na.approx(), na.fill(), etc to remove or replace them.
## [1] "DGS30"
## [1] "DGS1"
## [1] "DGS2"
## [1] "TB3MS"
## [1] "DTB3"
## [1] "^IRX"
## Warning: ^IRX contains missing values. Some functions will not work if objects
## contain missing values in the middle of the series. Consider using na.omit(),
## na.approx(), na.fill(), etc to remove or replace them.
## [1] "DCOILWTICO"
## [1] "DCOILBRENTEU"
## [1] "NEWORDER"
## [1] "ALTSALES"
## [1] "ICSA"
## [1] "^GSPC"
## [1] "FXAIX"
## [1] "FTIHX"
## [1] "MDIZX"
## [1] "DODIX"
## [1] "^RLG"
## Warning: ^RLG contains missing values. Some functions will not work if objects
## contain missing values in the middle of the series. Consider using na.omit(),
## na.approx(), na.fill(), etc to remove or replace them.
## [1] "^DJI"
## [1] "^STOXX50E"
## Warning: ^STOXX50E contains missing values. Some functions will not work if
## objects contain missing values in the middle of the series. Consider using
## na.omit(), na.approx(), na.fill(), etc to remove or replace them.
## [1] "EFA"
## [1] "GDP"
## [1] "FNDEFX"
## [1] "FDEFX"
## [1] "GDPNOW"
## [1] "GDPC1"
## [1] "GDPDEF"
## [1] "VIG"
## [1] "WLRRAL"
## [1] "FEDFUNDS"
## [1] "GPDI"
## [1] "W790RC1Q027SBEA"
## [1] "MZMV"
## [1] "M1"
## [1] "M2"
## [1] "OPHNFB"
## [1] "IPMAN"
## [1] "IWD"
## [1] "GS5"
## [1] "PSAVERT"
## [1] "VIXCLS"
## [1] "VXX"
## [1] "HOUST1F"
## [1] "GFDEBTN"
## [1] "HOUST"
## [1] "HOUSTNSA"
## [1] "EXHOSLUSM495S"
## [1] "MSPUS"
## [1] "UMDMNO"
## [1] "DGORDER"
## [1] "CSUSHPINSA"
## [1] "GFDEGDQ188S"
## [1] "FYFSD"
## [1] "FYFSGDA188S"
## [1] "GDX"
## [1] "XLE"
## [1] "GSG"
## [1] "WALCL"
## [1] "OUTMS"
## [1] "MANEMP"
## [1] "PRS30006163"
## [1] "BAMLC0A3CA"
## [1] "AAA"
## [1] "SOFR"
## [1] "SOFRVOL"
## [1] "SOFR99"
## [1] "SOFR75"
## [1] "SOFR25"
## [1] "SOFR1"
## [1] "OBFR"
## [1] "OBFR99"
## [1] "OBFR75"
## [1] "OBFR25"
## [1] "OBFR1"
## [1] "RPONTSYD"
## [1] "IOER"
## [1] "WRESBAL"
## [1] "EXCSRESNW"
## [1] "ECBASSETS"
## [1] "EUNNGDP"
## [1] "CEU0600000007"
## [1] "CURRENCY"
## [1] "WCURRNS"
## [1] "BOGMBASE"
## [1] "PRS88003193"
## [1] "PPIACO"
## [1] "PCUOMFGOMFG"
## [1] "POPTHM"
## [1] "POPTHM"
## [1] "CLF16OV"
## [1] "LNU01000000"
## [1] "LNU03000000"
## [1] "UNEMPLOY"
## [1] "RSAFS"
## [1] "FRGSHPUSM649NCIS"
## [1] "BOPGTB"
## [1] "TERMCBPER24NS"
## [1] "A065RC1A027NBEA"
## [1] "PI"
## [1] "PCE"
## [1] "A053RC1Q027SBEA"
## [1] "CPROFIT"
## [1] "SPY"
## [1] "MDY"
## [1] "EES"
## [1] "IJR"
## [1] "VGSTX"
## [1] "VFINX"
## [1] "VOE"
## [1] "VOT"
## [1] "TMFGX"
## Warning: TMFGX contains missing values. Some functions will not work if objects
## contain missing values in the middle of the series. Consider using na.omit(),
## na.approx(), na.fill(), etc to remove or replace them.
## [1] "IWM"
## [1] "ONEQ"
## [1] "FSMAX"
## [1] "FXNAX"
## [1] "HAINX"
## [1] "HNACX"
## [1] "VEU"
## [1] "VEIRX"
## [1] "BIL"
## [1] "IVOO"
## [1] "VO"
## [1] "CZA"
## [1] "VYM"
## [1] "ACWI"
## [1] "SLY"
## Warning: SLY contains missing values. Some functions will not work if objects
## contain missing values in the middle of the series. Consider using na.omit(),
## na.approx(), na.fill(), etc to remove or replace them.
## [1] "QQQ"
## [1] "HYMB"
## [1] "GOLD"
## [1] "BKR"
## [1] "SLB"
## [1] "HAL"
## [1] "IP"
## [1] "PKG"
## [1] "UPS"
## [1] "FDX"
## [1] "T"
## [1] "VZ"

Load up the EIA data

Load rig count data

The Baker Hughes rig count numbers

USDA data

Loading in farm data

## Warning in read_fun(path = enc2native(normalizePath(path)), sheet_i = sheet, :
## Expecting numeric in E3 / R3C5: got a date
## New names:
## * `` -> ...1
## * `` -> ...2
## * `` -> ...3
## * `` -> ...4
## * `` -> ...5
## * ...
## Warning: NAs introduced by coercion

Loading in Silverblatt’s S&P 500 spreadsheet starting with the quarterly data.

## New names:
## * `` -> ...2
## * `` -> ...3
## * `` -> ...5
## * `` -> ...6
## * `` -> ...7

Now load in the estimates

## New names:
## * `` -> ...2
## * `` -> ...3
## * `` -> ...4
## * `` -> ...5
## * `` -> ...6
## * ...

Covid 19 Data

Get the Covid-19 data from JHU

## Rows: 919308 Columns: 15
## -- Column specification ------------------------------------------------------------------------------------------------
## Delimiter: ","
## chr  (8): province, country, type, iso2, iso3, combined_key, continent_name,...
## dbl  (6): lat, long, cases, uid, code3, population
## date (1): date
## 
## i Use `spec()` to retrieve the full column specification for this data.
## i Specify the column types or set `show_col_types = FALSE` to quiet this message.
## Downloading GitHub repo RamiKrispin/coronavirus@master
##   
  
  
v  checking for file 'C:\Users\Rainy\AppData\Local\Temp\RtmpCaaLcn\remotes2d346bf288d\RamiKrispin-coronavirus-b286a3c/DESCRIPTION' (500ms)
## 
  
  
  
-  preparing 'coronavirus': (6.4s)
##    checking DESCRIPTION meta-information ...
  
   checking DESCRIPTION meta-information ... 
  
v  checking DESCRIPTION meta-information
## 
  
  
  
-  checking for LF line-endings in source and make files and shell scripts (625ms)
## 
  
  
  
-  checking for empty or unneeded directories
## 
  
  
  
-  building 'coronavirus_0.3.32.tar.gz'
## 
  
   
## 
## Caught an warning!
## <simpleWarning: package 'coronavirus' is in use and will not be installed>
## `summarise()` has grouped output by 'country'. You can override using the
## `.groups` argument.

## Warning: Removed 3 row(s) containing missing values (geom_path).

Feature Extraction

With the raw data downloaded, some of the interesting features can be extracted. The first step is reconcile the time intervals. Some of the data is released monthly and some daily. I chose to interpolate all data to a daily interval. The first section of code adds the daily rows to the dataframe.

The code performs interpolation for continuous data or carries it forward for binary data like the recession indicators.

source("calcInterpolate.r")
df.data <- calcInterpolate(df.symbols)
## Warning in merge.xts(xtsData, get(df.symbols$string.symbol[idx])): NAs
## introduced by coercion

## Warning in merge.xts(xtsData, get(df.symbols$string.symbol[idx])): NAs
## introduced by coercion

## Warning in merge.xts(xtsData, get(df.symbols$string.symbol[idx])): NAs
## introduced by coercion

Truncate data

Create aggregate series

Some analysis requires that two or more series be combined. For example, normallizing debt by GDP to get a sense of the proportion of debt to the total economy helps understand the debt cycle.

Year over year, smoothed derivative, and log trends tend to smooth out seasonal variation. It gets used so often that I do this for every series downloaded.

source("calcFeatures.r")
lst.df <- calcFeatures(df.data, df.symbols)
## [1] "USREC has zero or negative values. Log series will be zero."
## [1] "GSFTX.Volume has zero or negative values. Log series will be zero."
## [1] "LFMIX.Volume has zero or negative values. Log series will be zero."
## [1] "LFMCX.Volume has zero or negative values. Log series will be zero."
## [1] "LFMAX.Volume has zero or negative values. Log series will be zero."
## [1] "LCSIX.Volume has zero or negative values. Log series will be zero."
## [1] "VBIRX.Volume has zero or negative values. Log series will be zero."
## [1] "VFSUX.Volume has zero or negative values. Log series will be zero."
## [1] "LTUIX.Volume has zero or negative values. Log series will be zero."
## [1] "PTTPX.Volume has zero or negative values. Log series will be zero."
## [1] "NERYX.Volume has zero or negative values. Log series will be zero."
## [1] "STIGX.Volume has zero or negative values. Log series will be zero."
## [1] "HLGAX.Volume has zero or negative values. Log series will be zero."
## [1] "FTRGX.Volume has zero or negative values. Log series will be zero."
## [1] "THIIX.Volume has zero or negative values. Log series will be zero."
## [1] "PTTRX.Volume has zero or negative values. Log series will be zero."
## [1] "BFIGX.Volume has zero or negative values. Log series will be zero."
## [1] "EIFAX.Volume has zero or negative values. Log series will be zero."
## [1] "ASDAX.Volume has zero or negative values. Log series will be zero."
## [1] "TRBUX.Volume has zero or negative values. Log series will be zero."
## [1] "PRVIX.Volume has zero or negative values. Log series will be zero."
## [1] "PRWCX.Volume has zero or negative values. Log series will be zero."
## [1] "ADOZX.Volume has zero or negative values. Log series will be zero."
## [1] "MERFX.Volume has zero or negative values. Log series will be zero."
## [1] "CMNIX.Volume has zero or negative values. Log series will be zero."
## [1] "CIHEX.Volume has zero or negative values. Log series will be zero."
## [1] "SRPSABSNNCB has zero or negative values. Log series will be zero."
## [1] "TNX.Volume has zero or negative values. Log series will be zero."
## [1] "CLF.Open has zero or negative values. Log series will be zero."
## [1] "CLF.Low has zero or negative values. Log series will be zero."
## [1] "CLF.Close has zero or negative values. Log series will be zero."
## [1] "CLF.Volume has zero or negative values. Log series will be zero."
## [1] "CLF.Adjusted has zero or negative values. Log series will be zero."
## [1] "DTB3 has zero or negative values. Log series will be zero."
## [1] "IRX.Open has zero or negative values. Log series will be zero."
## [1] "IRX.High has zero or negative values. Log series will be zero."
## [1] "IRX.Low has zero or negative values. Log series will be zero."
## [1] "IRX.Close has zero or negative values. Log series will be zero."
## [1] "IRX.Volume has zero or negative values. Log series will be zero."
## [1] "IRX.Adjusted has zero or negative values. Log series will be zero."
## [1] "DCOILWTICO has zero or negative values. Log series will be zero."
## [1] "GSPC.Volume has zero or negative values. Log series will be zero."
## [1] "FXAIX.Volume has zero or negative values. Log series will be zero."
## [1] "FTIHX.Volume has zero or negative values. Log series will be zero."
## [1] "MDIZX.Volume has zero or negative values. Log series will be zero."
## [1] "DODIX.Volume has zero or negative values. Log series will be zero."
## [1] "RLG.Volume has zero or negative values. Log series will be zero."
## [1] "STOXX50E.Volume has zero or negative values. Log series will be zero."
## [1] "GDPNOW has zero or negative values. Log series will be zero."
## [1] "W790RC1Q027SBEA has zero or negative values. Log series will be zero."
## [1] "VXX.Volume has zero or negative values. Log series will be zero."
## [1] "FYFSD has zero or negative values. Log series will be zero."
## [1] "FYFSGDA188S has zero or negative values. Log series will be zero."
## [1] "SOFR25 has zero or negative values. Log series will be zero."
## [1] "SOFR1 has zero or negative values. Log series will be zero."
## [1] "RPONTSYD has zero or negative values. Log series will be zero."
## [1] "BOPGTB has zero or negative values. Log series will be zero."
## [1] "EES.Volume has zero or negative values. Log series will be zero."
## [1] "VGSTX.Volume has zero or negative values. Log series will be zero."
## [1] "VFINX.Volume has zero or negative values. Log series will be zero."
## [1] "TMFGX.Volume has zero or negative values. Log series will be zero."
## [1] "FSMAX.Volume has zero or negative values. Log series will be zero."
## [1] "FXNAX.Volume has zero or negative values. Log series will be zero."
## [1] "HAINX.Volume has zero or negative values. Log series will be zero."
## [1] "HNACX.Volume has zero or negative values. Log series will be zero."
## [1] "VEIRX.Volume has zero or negative values. Log series will be zero."
## [1] "IVOO.Volume has zero or negative values. Log series will be zero."
## [1] "VO.Volume has zero or negative values. Log series will be zero."
## [1] "CZA.Volume has zero or negative values. Log series will be zero."
## [1] "SLY.Volume has zero or negative values. Log series will be zero."
## [1] "HYMB.Volume has zero or negative values. Log series will be zero."
## [1] "GOLD.Open has zero or negative values. Log series will be zero."
## [1] "GOLD.Volume has zero or negative values. Log series will be zero."
## [1] "BKR.Open has zero or negative values. Log series will be zero."
## [1] "BKR.Volume has zero or negative values. Log series will be zero."
## [1] "HAL.Open has zero or negative values. Log series will be zero."
## [1] "HAL.Volume has zero or negative values. Log series will be zero."
## [1] "IP.Open has zero or negative values. Log series will be zero."
## [1] "T.Open has zero or negative values. Log series will be zero."
## [1] "OPEARNINGSPERSHARE has zero or negative values. Log series will be zero."
## [1] "AREARNINGSPERSHARE has zero or negative values. Log series will be zero."
## [1] "OCCEquityVolume has zero or negative values. Log series will be zero."
## [1] "OCCNonEquityVolume has zero or negative values. Log series will be zero."
## [1] "BUSLOANS.minus.BUSLOANSNSA has zero or negative values. Log series will be zero."
## [1] "BUSLOANS.minus.BUSLOANSNSA.by.GDP has zero or negative values. Log series will be zero."
## [1] "EXPCH.minus.IMPCH has zero or negative values. Log series will be zero."
## [1] "EXPMX.minus.IMPMX has zero or negative values. Log series will be zero."
## [1] "SRPSABSNNCB.by.GDP has zero or negative values. Log series will be zero."
## [1] "DGS30TO10 has zero or negative values. Log series will be zero."
## [1] "DGS10TO1 has zero or negative values. Log series will be zero."
## [1] "DGS10TO2 has zero or negative values. Log series will be zero."
## [1] "DGS10TOTB3MS has zero or negative values. Log series will be zero."
## [1] "DGS10TODTB3 has zero or negative values. Log series will be zero."
## [1] "DCOILWTICO.by.PPIACO has zero or negative values. Log series will be zero."
## [1] "GSPC.DailySwing has zero or negative values. Log series will be zero."
df.data <- lst.df[[1]]
df.symbols <- lst.df[[2]]

Recession calculations

Summary calculations

These values are used below

Conclusion

In this worksheet a model predicting the onset of recession was built. From the model a trading rule was derived to allow backtesting. The model performed well and the trading rule backtesting showed that applying this in the post-WWII period would have resulted in an increase in returns. That is not too bad, but there are a few changes that would likely improve the model:

Market Conditions

#The model is predicting a `r paste(sprintf("%3.0f", tail(df.data$recession.initiation.smooth.avg,1)[[1]]*100), "%", sep="")` chance of recession in the next 12 months. :

#- P/E ratio of `r sprintf("%3.2f", tail(df.data$MULTPLSP500PERATIOMONTH,1))` compares to a historical mean value over the last decade of `r sprintf("%3.2f", df.data$MULTPLSP500PERATIOMONTH_Mean[1])`. Since 2008 recession P/E has only fallen below historical norm a few times. The current value is high, but well off the peaks. If earnings are +2-4% year-over-year then it is not unrealistic.

As of Feb 2020 we have entered a recession as defined by the NBER yet the market continues to rise.

P/E ratio of 23.62 compares to a historical mean value over the last decade of 18.73. Since 2008 recession P/E has only fallen below historical norm a few times. The current value is high, but well off the peaks. If earnings are +2-4% year-over-year then it is not unrealistic.

  • S&P 500 Volume, last updated on 2023-11-21, is flat over the last year and negative over the last month.

Unemployment

  • Headline unemployment (U-3) stands at 3.90% (last updated on 2023-10-01) which is near the 1-year average of 3.64% and rising with respect to the low in the last twelve months of 3.40%. Unlikely the rate will drop again.

  • Payrolls (BLS data, NSA) year-over-year stands at 1.63% which is above the 1-year average of 2.41% and falling with respect to the peak, in the last twelve months, of 3.32%.

  • Jobless claims (ICSA data) year-over-year stands at -3.81% (last updated on 2023-11-18) which is in-line with the 1-year average of 5.31% and below the peak, in the last twelve months, of 22.60%.
## Warning: Removed 1 rows containing missing values (geom_text).
## Warning: Removed 1 rows containing missing values (geom_hline).

Personal Income

  • Real personal income year over year growth stands at 2.06% (last updated on 2023-09-01). This is below the recent peak of 2.70%.

Yield Curve and Bond Market

  • The 10-year to 3-month yield stands at -0.85% (last updated on 2023-11-20). This is above the recent low of -1.73%. The trend is flat over the last year and positive over the last month.
## Warning: Removed 1 rows containing missing values (geom_text).
## Warning: Removed 1 rows containing missing values (geom_hline).

  • Auto sales flat?

Auxillary Series

I explored additional data series. The sections below have those data series along with comments.

Recent Highs

Print out the new 180 day high values

df.symbolsTrue <-
  df.symbols[df.symbols$'Max180' == TRUE, c("string.symbol", "string.description")]
df.symbolsTrue <-
  df.symbolsTrue[!(is.na(df.symbolsTrue$string.symbol)), ]
df.symbolsTrue <-
  df.symbolsTrue[!(df.symbolsTrue$string.symbol == 'USREC'), ]
#print(head(df.symbolsTrue,20))

kable(df.symbolsTrue, caption = "6-Month High") %>%
  kable_styling(bootstrap_options = c("striped", "hover"))  
6-Month High
string.symbol string.description
1 CPIAUCSL Consumer Price Index for All Urban Consumers: All Items
3 UNRATE Civilian Unemployment Rate U-3
4 PCEPI Personal Consumption Expenditures: Chain-type Price Index
7 NPPTTL Total Nonfarm Private Payroll Employment (ADP)
8 U6RATE Total unemployed + margin + part-time U-6
9 PAYNSA All Employees: Total Nonfarm Payrolls (NSA)
10 TABSHNO Households and nonprofit organizations; total assets, Level
11 HNONWPDPI Household Net Worth, percent Dispsable Income
14 RSALES Real Retail Sales (DISCONTINUED)
15 W875RX1 Real personal income excluding current transfer receipts
50 IMPCH U.S. Imports of Goods by Customs Basis from China (Monthly, NSA)
51 EXPCH U.S. Exports of Goods by F.A.S. Basis to China, Mainland (Monthly, NSA)
55 HNFSUSNSA New One Family Houses for Sale in the United States (Monthly, NSA)
56 BUSLOANS Commercial and Industrial Loans, All Commercial Banks (Monthly, SA)
59 REALLNNSA Real Estate Loans, All Commercial Banks (Monthly, NSA)
60 REALLN Real Estate Loans, All Commercial Banks (Monthly, SA)
61 RELACBW027NBOG Real Estate Loans, All Commercial Banks (Weekly, NSA)
63 RREACBM027NBOG Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Monthly, NSA)
66 RREACBW027NBOG Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Weekly, NSA)
68 CONSUMERNSA Consumer Loans, All Commercial Banks
71 DRCLACBS Delinquency Rate on Consumer Loans, All Commercial Banks, SA
73 SRPSABSNNCB Nonfinancial corporate business; security repurchase agreements; asset, Level (NSA)
74 ASTLL All sectors; total loans; liability, Level (NSA)
75 FBDILNECA Domestic financial sectors; depository institution loans n.e.c.; asset, Level (NSA)
76 ASOLAL All sectors; other loans and advances; liability, Level (NSA)
77 ASTMA All sectors; total mortgages; asset, Level (NSA)
78 ASHMA All sectors; home mortgages; asset, Level (NSA)
79 ASMRMA All sectors; multifamily residential mortgages; asset, Level (NSA)
80 ASCMA All sectors; commercial mortgages; asset, Level (NSA)
81 ASFMA All sectors; farm mortgages; asset, Level (NSA)
82 CCLBSHNO Households and nonprofit organizations; consumer credit; liability, Level (NSA)
83 FBDSILQ027S Domestic financial sectors debt securities; liability, Level (NSA)
84 FBLL Domestic financial sectors loans; liability, Level (NSA)
85 NCBDBIQ027S Nonfinancial corporate business; debt securities; liability, Level
92 TB3MS 3-Month Treasury Bill: Secondary Market Rate (Monthly)
109 GDP Gross Domestic Product
110 FNDEFX Federal Government: Nondefense Consumption Expenditures and Gross Investment (SA, Annual Rate)
111 FDEFX Federal Government: National Defense Consumption Expenditures and Gross Investment (SA, Annual Rate)
113 GDPC1 Real Gross Domestic Product
114 GDPDEF Gross Domestic Product: Implicit Price Deflator
117 FEDFUNDS Effective Federal Funds Rate
118 GPDI Gross Private Domestic Investment
119 W790RC1Q027SBEA Net domestic investment: Private: Domestic busines
120 MZMV Velocity of MZM Money Stock
121 M1 M1 Money Stock
122 M2 M2 Money Stock
123 OPHNFB Nonfarm Business Sector: Real Output Per Hour of All Persons, SA
126 GS5 5-Year Treasury Constant Maturity Rate
131 GFDEBTN Federal Debt: Total Public Debt
135 MSPUS Median Sales Price of Houses Sold for the United States (NSA)
138 CSUSHPINSA S&P/Case-Shiller U.S. National Home Price Index (NSA)
139 GFDEGDQ188S Federal Debt: Total Public Debt as Percent of Gross Domestic Product
141 FYFSGDA188S Federal Surplus or Deficit [-] as Percent of Gross Domestic Product
150 AAA Moody’s Seasoned Aaa Corporate Bond Yield
157 OBFR Overnight Bank Funding Rate
159 OBFR75 Overnight Bank Funding Rate: 75th Percentile
160 OBFR25 Overnight Bank Funding Rate: 25th Percentile
163 IOER Interest Rate on Excess Reserves
164 WRESBAL Reserve Balances with Federal Reserve Banks
165 EXCSRESNW Excess Reserves of Depository Institutions
166 ECBASSETS Central Bank Assets for Euro Area (11-19 Countries)
167 EUNNGDP Gross Domestic Product (Euro/ECU series) for Euro Area (19 Countries)
168 CEU0600000007 Average Weekly Hours of Production and Nonsupervisory Employees: Goods-Producing
169 CURRENCY Currency Component of M1 (Seasonally Adjusted)
172 PRS88003193 Nonfinancial Corporations Sector: Unit Profits
175 POPTHM Population (U.S.)
176 POPTHM Population (U.S.)
180 UNEMPLOY Unemployment Level, seasonally adjusted
184 TERMCBPER24NS Finance Rate on Personal Loans at Commercial Banks, 24 Month Loan
185 A065RC1A027NBEA Personal income (NSA)
186 PI Personal income (SA)
187 PCE Personal Consumption Expenditures (SA)
188 A053RC1Q027SBEA National income: Corporate profits before tax (without IVA and CCAdj)
189 CPROFIT Corporate Profits with Inventory Valuation Adjustment (IVA) and Capital Consumption Adjustment (CCAdj)
226 ISMMANPMI Institute of Supply Managment PMI Composite Index
228 MULTPLSP500SALESQUARTER S&P 500 TTM Sales (Not Inflation Adjusted)
231 CHRISCMEHG1 Copper Futures, Continuous Contract #1 (HG1) (Front Month)
232 WWDIWLDISAIRGOODMTK1 Air transport, freight
234 PETA103600001M U.S. Total Gasoline Retail Sales by Refiners, Monthly
235 PETA123600001M U.S. Regular Gasoline Retail Sales by Refiners, Monthly
236 PETA143B00001M U.S. Midgrade Gasoline Retail Sales by Refiners, Monthly
237 PETA133B00001M U.S. Premium Gasoline Bulk Sales (Volume) by Refiners, Monthly
241 BKRTotal Total Rig Count
242 BKRGas Gas Rig Count
243 BKROil Oil Rig Count
244 FARMINCOME Net Farm Income
245 OPEARNINGSPERSHARE Operating Earnings per Share
246 AREARNINGSPERSHARE As-Reported Earnings per Share
247 CASHDIVIDENDSPERSHR Cash Dividends per Share
248 SALESPERSHR Sales per Share
249 BOOKVALPERSHR Book value per Share
250 CAPEXPERSHR Cap ex per Share
251 PRICE Price
252 OPEARNINGSTTM TTM Operating Earnings
253 AREARNINGSTTM TTM Reported Earnings
254 FINRAMarginDebt Margin Debt
256 OCCEquityVolume Equity Options Volume
257 OCCNonEquityVolume Non-Equity Options Volume
271 PI.by.GDP Personal Income (SA) Normalized by GDP
274 CONSUMERNSA.by.GDP Consumer Loans Not Seasonally Adjusted divided by GDP
275 RREACBM027NBOG.by.GDP Residental Real Estate Loans (Monthly, NSA) divided by GDP
278 RREACBW027NBOG.by.GDP Residental Real Estate Loans (Weekly, NSA) divided by GDP
284 CONSUMERNSA.INTEREST Consumer Loans (Not Seasonally Adjusted) Interest Burdens
285 CONSUMERNSA.INTEREST.by.GDP Consumer Loans (Not Seasonally Adjusted) Interest Burden Divided by GDP
286 TOTLNNSA Total Loans Not Seasonally Adjusted (BUSLOANS+REALLNSA+CONSUMERNSA)
287 TOTLNNSA.by.GDP Total Loans Not Seasonally Adjusted divided by GDP
290 WRESBAL.by.GDP Reserve Balances with Federal Reserve Banks Divided by GDP
299 ASFMA.by.ASTLL All sectors; total loans Divided by farm mortgages
305 ECBASSETS.by.EUNNGDP Central Bank Assets for Euro Area (11-19 Countries) Divided by GDP
313 UNEMPLOYBYPOPTHM Unemployment level, seasonally adjusted / Population
315 U6toU3 U6RATE minums UNRATE
320 LBMAGOLD.USD_PM.by.PPIACO Gold, USD PM/Troy Ounce, Normalized by commodities producer price index
321 LBMAGOLD.USD_PM.by.CPIAUCSL Gold, USD/Troy OUnce, Normalized by consumer price index
322 LBMAGOLD.USD_PM.by.GDP Gold, USD/Troy OUnce, Normalized by GDP
323 GDP.by.GDPDEF Nominal GDP Normalized by GDP def
337 MSPUS.times.HNFSUSNSA New privately owned 1-family units for sale times median price
343 CPIAUCSL_Smooth Savitsky-Golay Smoothed (p=3, n=365) Consumer Price Index for All Urban Consumers: All Items
346 CPIAUCSL_Log Log of Consumer Price Index for All Urban Consumers: All Items
347 CPIAUCSL_mva365 Consumer Price Index for All Urban Consumers: All Items 365 Day MA
348 CPIAUCSL_mva200 Consumer Price Index for All Urban Consumers: All Items 200 Day MA
349 CPIAUCSL_mva050 Consumer Price Index for All Urban Consumers: All Items 50 Day MA
350 USREC_YoY NBER based Recession Indicators Year over Year
351 USREC_YoY4 NBER based Recession Indicators 4 Year over 4 Year
352 USREC_YoY5 NBER based Recession Indicators 5 Year over 5 Year
353 USREC_Smooth Savitsky-Golay Smoothed (p=3, n=365) NBER based Recession Indicators
354 USREC_Smooth.short Savitsky-Golay Smoothed (p=3, n=15) NBER based Recession Indicators
355 USREC_SmoothDer Derivative of Smoothed NBER based Recession Indicators
356 USREC_Log Log of NBER based Recession Indicators
357 USREC_mva365 NBER based Recession Indicators 365 Day MA
358 USREC_mva200 NBER based Recession Indicators 200 Day MA
359 USREC_mva050 NBER based Recession Indicators 50 Day MA
360 UNRATE_YoY Civilian Unemployment Rate U-3 Year over Year
363 UNRATE_Smooth Savitsky-Golay Smoothed (p=3, n=365) Civilian Unemployment Rate U-3
365 UNRATE_SmoothDer Derivative of Smoothed Civilian Unemployment Rate U-3
366 UNRATE_Log Log of Civilian Unemployment Rate U-3
367 UNRATE_mva365 Civilian Unemployment Rate U-3 365 Day MA
368 UNRATE_mva200 Civilian Unemployment Rate U-3 200 Day MA
369 UNRATE_mva050 Civilian Unemployment Rate U-3 50 Day MA
373 PCEPI_Smooth Savitsky-Golay Smoothed (p=3, n=365) Personal Consumption Expenditures: Chain-type Price Index
376 PCEPI_Log Log of Personal Consumption Expenditures: Chain-type Price Index
377 PCEPI_mva365 Personal Consumption Expenditures: Chain-type Price Index 365 Day MA
378 PCEPI_mva200 Personal Consumption Expenditures: Chain-type Price Index 200 Day MA
379 PCEPI_mva050 Personal Consumption Expenditures: Chain-type Price Index 50 Day MA
383 CCSA_Smooth Savitsky-Golay Smoothed (p=3, n=365) Continued Claims (Insured Unemployment)
387 CCSA_mva365 Continued Claims (Insured Unemployment) 365 Day MA
389 CCSA_mva050 Continued Claims (Insured Unemployment) 50 Day MA
397 CCNSA_mva365 Continued Claims (Insured Unemployment, NSA) 365 Day MA
400 NPPTTL_YoY Total Nonfarm Private Payroll Employment (ADP) Year over Year
406 NPPTTL_Log Log of Total Nonfarm Private Payroll Employment (ADP)
407 NPPTTL_mva365 Total Nonfarm Private Payroll Employment (ADP) 365 Day MA
408 NPPTTL_mva200 Total Nonfarm Private Payroll Employment (ADP) 200 Day MA
409 NPPTTL_mva050 Total Nonfarm Private Payroll Employment (ADP) 50 Day MA
410 U6RATE_YoY Total unemployed + margin + part-time U-6 Year over Year
411 U6RATE_YoY4 Total unemployed + margin + part-time U-6 4 Year over 4 Year
413 U6RATE_Smooth Savitsky-Golay Smoothed (p=3, n=365) Total unemployed + margin + part-time U-6
416 U6RATE_Log Log of Total unemployed + margin + part-time U-6
417 U6RATE_mva365 Total unemployed + margin + part-time U-6 365 Day MA
418 U6RATE_mva200 Total unemployed + margin + part-time U-6 200 Day MA
419 U6RATE_mva050 Total unemployed + margin + part-time U-6 50 Day MA
425 PAYNSA_SmoothDer Derivative of Smoothed All Employees: Total Nonfarm Payrolls (NSA)
426 PAYNSA_Log Log of All Employees: Total Nonfarm Payrolls (NSA)
427 PAYNSA_mva365 All Employees: Total Nonfarm Payrolls (NSA) 365 Day MA
428 PAYNSA_mva200 All Employees: Total Nonfarm Payrolls (NSA) 200 Day MA
429 PAYNSA_mva050 All Employees: Total Nonfarm Payrolls (NSA) 50 Day MA
436 TABSHNO_Log Log of Households and nonprofit organizations; total assets, Level
437 TABSHNO_mva365 Households and nonprofit organizations; total assets, Level 365 Day MA
438 TABSHNO_mva200 Households and nonprofit organizations; total assets, Level 200 Day MA
439 TABSHNO_mva050 Households and nonprofit organizations; total assets, Level 50 Day MA
440 HNONWPDPI_YoY Household Net Worth, percent Dispsable Income Year over Year
441 HNONWPDPI_YoY4 Household Net Worth, percent Dispsable Income 4 Year over 4 Year
446 HNONWPDPI_Log Log of Household Net Worth, percent Dispsable Income
447 HNONWPDPI_mva365 Household Net Worth, percent Dispsable Income 365 Day MA
448 HNONWPDPI_mva200 Household Net Worth, percent Dispsable Income 200 Day MA
449 HNONWPDPI_mva050 Household Net Worth, percent Dispsable Income 50 Day MA
450 INDPRO_YoY Industrial Production Index Year over Year
460 RRSFS_YoY Real Retail and Food Services Sales Year over Year
462 RRSFS_YoY5 Real Retail and Food Services Sales 5 Year over 5 Year
463 RRSFS_Smooth Savitsky-Golay Smoothed (p=3, n=365) Real Retail and Food Services Sales
465 RRSFS_SmoothDer Derivative of Smoothed Real Retail and Food Services Sales
468 RRSFS_mva200 Real Retail and Food Services Sales 200 Day MA
470 RSALES_YoY Real Retail Sales (DISCONTINUED) Year over Year
471 RSALES_YoY4 Real Retail Sales (DISCONTINUED) 4 Year over 4 Year
472 RSALES_YoY5 Real Retail Sales (DISCONTINUED) 5 Year over 5 Year
476 RSALES_Log Log of Real Retail Sales (DISCONTINUED)
477 RSALES_mva365 Real Retail Sales (DISCONTINUED) 365 Day MA
478 RSALES_mva200 Real Retail Sales (DISCONTINUED) 200 Day MA
479 RSALES_mva050 Real Retail Sales (DISCONTINUED) 50 Day MA
483 W875RX1_Smooth Savitsky-Golay Smoothed (p=3, n=365) Real personal income excluding current transfer receipts
486 W875RX1_Log Log of Real personal income excluding current transfer receipts
487 W875RX1_mva365 Real personal income excluding current transfer receipts 365 Day MA
488 W875RX1_mva200 Real personal income excluding current transfer receipts 200 Day MA
489 W875RX1_mva050 Real personal income excluding current transfer receipts 50 Day MA
497 RPI_mva365 Real personal income 365 Day MA
498 RPI_mva200 Real personal income 200 Day MA
553 NOBL.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
555 NOBL.Volume_SmoothDer Derivative of Smoothed
558 NOBL.Volume_mva200 200 Day MA
613 SCHD.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
615 SCHD.Volume_SmoothDer Derivative of Smoothed
673 PFF.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
675 PFF.Volume_SmoothDer Derivative of Smoothed
692 HPI.Open_YoY5 5 Year over 5 Year
702 HPI.High_YoY5 5 Year over 5 Year
712 HPI.Low_YoY5 5 Year over 5 Year
733 HPI.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
734 HPI.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
735 HPI.Volume_SmoothDer Derivative of Smoothed
739 HPI.Volume_mva050 50 Day MA
758 GSFTX.Open_mva200 200 Day MA
768 GSFTX.High_mva200 200 Day MA
778 GSFTX.Low_mva200 200 Day MA
788 GSFTX.Close_mva200 200 Day MA
790 GSFTX.Volume_YoY Year over Year
791 GSFTX.Volume_YoY4 4 Year over 4 Year
792 GSFTX.Volume_YoY5 5 Year over 5 Year
793 GSFTX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
794 GSFTX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
795 GSFTX.Volume_SmoothDer Derivative of Smoothed
796 GSFTX.Volume_Log Log of
797 GSFTX.Volume_mva365 365 Day MA
798 GSFTX.Volume_mva200 200 Day MA
799 GSFTX.Volume_mva050 50 Day MA
807 GSFTX.Adjusted_mva365 365 Day MA
808 GSFTX.Adjusted_mva200 200 Day MA
815 LFMIX.Open_SmoothDer Derivative of Smoothed
825 LFMIX.High_SmoothDer Derivative of Smoothed
835 LFMIX.Low_SmoothDer Derivative of Smoothed
845 LFMIX.Close_SmoothDer Derivative of Smoothed
850 LFMIX.Volume_YoY Year over Year
851 LFMIX.Volume_YoY4 4 Year over 4 Year
852 LFMIX.Volume_YoY5 5 Year over 5 Year
853 LFMIX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
854 LFMIX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
855 LFMIX.Volume_SmoothDer Derivative of Smoothed
856 LFMIX.Volume_Log Log of
857 LFMIX.Volume_mva365 365 Day MA
858 LFMIX.Volume_mva200 200 Day MA
859 LFMIX.Volume_mva050 50 Day MA
863 LFMIX.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
865 LFMIX.Adjusted_SmoothDer Derivative of Smoothed
875 LFMCX.Open_SmoothDer Derivative of Smoothed
885 LFMCX.High_SmoothDer Derivative of Smoothed
895 LFMCX.Low_SmoothDer Derivative of Smoothed
905 LFMCX.Close_SmoothDer Derivative of Smoothed
910 LFMCX.Volume_YoY Year over Year
911 LFMCX.Volume_YoY4 4 Year over 4 Year
912 LFMCX.Volume_YoY5 5 Year over 5 Year
913 LFMCX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
914 LFMCX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
915 LFMCX.Volume_SmoothDer Derivative of Smoothed
916 LFMCX.Volume_Log Log of
917 LFMCX.Volume_mva365 365 Day MA
918 LFMCX.Volume_mva200 200 Day MA
919 LFMCX.Volume_mva050 50 Day MA
923 LFMCX.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
925 LFMCX.Adjusted_SmoothDer Derivative of Smoothed
935 LFMAX.Open_SmoothDer Derivative of Smoothed
945 LFMAX.High_SmoothDer Derivative of Smoothed
955 LFMAX.Low_SmoothDer Derivative of Smoothed
965 LFMAX.Close_SmoothDer Derivative of Smoothed
970 LFMAX.Volume_YoY Year over Year
971 LFMAX.Volume_YoY4 4 Year over 4 Year
972 LFMAX.Volume_YoY5 5 Year over 5 Year
973 LFMAX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
974 LFMAX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
975 LFMAX.Volume_SmoothDer Derivative of Smoothed
976 LFMAX.Volume_Log Log of
977 LFMAX.Volume_mva365 365 Day MA
978 LFMAX.Volume_mva200 200 Day MA
979 LFMAX.Volume_mva050 50 Day MA
983 LFMAX.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
985 LFMAX.Adjusted_SmoothDer Derivative of Smoothed
995 LCSIX.Open_SmoothDer Derivative of Smoothed
1005 LCSIX.High_SmoothDer Derivative of Smoothed
1015 LCSIX.Low_SmoothDer Derivative of Smoothed
1025 LCSIX.Close_SmoothDer Derivative of Smoothed
1030 LCSIX.Volume_YoY Year over Year
1031 LCSIX.Volume_YoY4 4 Year over 4 Year
1032 LCSIX.Volume_YoY5 5 Year over 5 Year
1033 LCSIX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1034 LCSIX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
1035 LCSIX.Volume_SmoothDer Derivative of Smoothed
1036 LCSIX.Volume_Log Log of
1037 LCSIX.Volume_mva365 365 Day MA
1038 LCSIX.Volume_mva200 200 Day MA
1039 LCSIX.Volume_mva050 50 Day MA
1045 LCSIX.Adjusted_SmoothDer Derivative of Smoothed
1095 BSV.Volume_SmoothDer Derivative of Smoothed
1103 BSV.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1106 BSV.Adjusted_Log Log of
1107 BSV.Adjusted_mva365 365 Day MA
1150 VBIRX.Volume_YoY Year over Year
1151 VBIRX.Volume_YoY4 4 Year over 4 Year
1152 VBIRX.Volume_YoY5 5 Year over 5 Year
1153 VBIRX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1154 VBIRX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
1155 VBIRX.Volume_SmoothDer Derivative of Smoothed
1156 VBIRX.Volume_Log Log of
1157 VBIRX.Volume_mva365 365 Day MA
1158 VBIRX.Volume_mva200 200 Day MA
1159 VBIRX.Volume_mva050 50 Day MA
1167 VBIRX.Adjusted_mva365 365 Day MA
1213 BIV.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1215 BIV.Volume_SmoothDer Derivative of Smoothed
1219 BIV.Volume_mva050 50 Day MA
1232 VFSUX.Open_YoY5 5 Year over 5 Year
1242 VFSUX.High_YoY5 5 Year over 5 Year
1252 VFSUX.Low_YoY5 5 Year over 5 Year
1262 VFSUX.Close_YoY5 5 Year over 5 Year
1270 VFSUX.Volume_YoY Year over Year
1271 VFSUX.Volume_YoY4 4 Year over 4 Year
1272 VFSUX.Volume_YoY5 5 Year over 5 Year
1273 VFSUX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1274 VFSUX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
1275 VFSUX.Volume_SmoothDer Derivative of Smoothed
1276 VFSUX.Volume_Log Log of
1277 VFSUX.Volume_mva365 365 Day MA
1278 VFSUX.Volume_mva200 200 Day MA
1279 VFSUX.Volume_mva050 50 Day MA
1287 VFSUX.Adjusted_mva365 365 Day MA
1330 LTUIX.Volume_YoY Year over Year
1331 LTUIX.Volume_YoY4 4 Year over 4 Year
1332 LTUIX.Volume_YoY5 5 Year over 5 Year
1333 LTUIX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1334 LTUIX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
1335 LTUIX.Volume_SmoothDer Derivative of Smoothed
1336 LTUIX.Volume_Log Log of
1337 LTUIX.Volume_mva365 365 Day MA
1338 LTUIX.Volume_mva200 200 Day MA
1339 LTUIX.Volume_mva050 50 Day MA
1390 PTTPX.Volume_YoY Year over Year
1391 PTTPX.Volume_YoY4 4 Year over 4 Year
1392 PTTPX.Volume_YoY5 5 Year over 5 Year
1393 PTTPX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1394 PTTPX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
1395 PTTPX.Volume_SmoothDer Derivative of Smoothed
1396 PTTPX.Volume_Log Log of
1397 PTTPX.Volume_mva365 365 Day MA
1398 PTTPX.Volume_mva200 200 Day MA
1399 PTTPX.Volume_mva050 50 Day MA
1450 NERYX.Volume_YoY Year over Year
1451 NERYX.Volume_YoY4 4 Year over 4 Year
1452 NERYX.Volume_YoY5 5 Year over 5 Year
1453 NERYX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1454 NERYX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
1455 NERYX.Volume_SmoothDer Derivative of Smoothed
1456 NERYX.Volume_Log Log of
1457 NERYX.Volume_mva365 365 Day MA
1458 NERYX.Volume_mva200 200 Day MA
1459 NERYX.Volume_mva050 50 Day MA
1510 STIGX.Volume_YoY Year over Year
1511 STIGX.Volume_YoY4 4 Year over 4 Year
1512 STIGX.Volume_YoY5 5 Year over 5 Year
1513 STIGX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1514 STIGX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
1515 STIGX.Volume_SmoothDer Derivative of Smoothed
1516 STIGX.Volume_Log Log of
1517 STIGX.Volume_mva365 365 Day MA
1518 STIGX.Volume_mva200 200 Day MA
1519 STIGX.Volume_mva050 50 Day MA
1570 HLGAX.Volume_YoY Year over Year
1571 HLGAX.Volume_YoY4 4 Year over 4 Year
1572 HLGAX.Volume_YoY5 5 Year over 5 Year
1573 HLGAX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1574 HLGAX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
1575 HLGAX.Volume_SmoothDer Derivative of Smoothed
1576 HLGAX.Volume_Log Log of
1577 HLGAX.Volume_mva365 365 Day MA
1578 HLGAX.Volume_mva200 200 Day MA
1579 HLGAX.Volume_mva050 50 Day MA
1630 FTRGX.Volume_YoY Year over Year
1631 FTRGX.Volume_YoY4 4 Year over 4 Year
1632 FTRGX.Volume_YoY5 5 Year over 5 Year
1633 FTRGX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1634 FTRGX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
1635 FTRGX.Volume_SmoothDer Derivative of Smoothed
1636 FTRGX.Volume_Log Log of
1637 FTRGX.Volume_mva365 365 Day MA
1638 FTRGX.Volume_mva200 200 Day MA
1639 FTRGX.Volume_mva050 50 Day MA
1690 THIIX.Volume_YoY Year over Year
1691 THIIX.Volume_YoY4 4 Year over 4 Year
1692 THIIX.Volume_YoY5 5 Year over 5 Year
1693 THIIX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1694 THIIX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
1695 THIIX.Volume_SmoothDer Derivative of Smoothed
1696 THIIX.Volume_Log Log of
1697 THIIX.Volume_mva365 365 Day MA
1698 THIIX.Volume_mva200 200 Day MA
1699 THIIX.Volume_mva050 50 Day MA
1707 THIIX.Adjusted_mva365 365 Day MA
1750 PTTRX.Volume_YoY Year over Year
1751 PTTRX.Volume_YoY4 4 Year over 4 Year
1752 PTTRX.Volume_YoY5 5 Year over 5 Year
1753 PTTRX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1754 PTTRX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
1755 PTTRX.Volume_SmoothDer Derivative of Smoothed
1756 PTTRX.Volume_Log Log of
1757 PTTRX.Volume_mva365 365 Day MA
1758 PTTRX.Volume_mva200 200 Day MA
1759 PTTRX.Volume_mva050 50 Day MA
1810 BFIGX.Volume_YoY Year over Year
1811 BFIGX.Volume_YoY4 4 Year over 4 Year
1812 BFIGX.Volume_YoY5 5 Year over 5 Year
1813 BFIGX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1814 BFIGX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
1815 BFIGX.Volume_SmoothDer Derivative of Smoothed
1816 BFIGX.Volume_Log Log of
1817 BFIGX.Volume_mva365 365 Day MA
1818 BFIGX.Volume_mva200 200 Day MA
1819 BFIGX.Volume_mva050 50 Day MA
1873 VTWO.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1875 VTWO.Volume_SmoothDer Derivative of Smoothed
1877 VTWO.Volume_mva365 365 Day MA
1878 VTWO.Volume_mva200 200 Day MA
1879 VTWO.Volume_mva050 50 Day MA
1893 EIFAX.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1897 EIFAX.Open_mva365 365 Day MA
1898 EIFAX.Open_mva200 200 Day MA
1903 EIFAX.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1907 EIFAX.High_mva365 365 Day MA
1908 EIFAX.High_mva200 200 Day MA
1913 EIFAX.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1917 EIFAX.Low_mva365 365 Day MA
1918 EIFAX.Low_mva200 200 Day MA
1923 EIFAX.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1927 EIFAX.Close_mva365 365 Day MA
1928 EIFAX.Close_mva200 200 Day MA
1930 EIFAX.Volume_YoY Year over Year
1931 EIFAX.Volume_YoY4 4 Year over 4 Year
1932 EIFAX.Volume_YoY5 5 Year over 5 Year
1933 EIFAX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1934 EIFAX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
1935 EIFAX.Volume_SmoothDer Derivative of Smoothed
1936 EIFAX.Volume_Log Log of
1937 EIFAX.Volume_mva365 365 Day MA
1938 EIFAX.Volume_mva200 200 Day MA
1939 EIFAX.Volume_mva050 50 Day MA
1943 EIFAX.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1947 EIFAX.Adjusted_mva365 365 Day MA
1948 EIFAX.Adjusted_mva200 200 Day MA
1953 ASDAX.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1954 ASDAX.Open_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
1956 ASDAX.Open_Log Log of
1957 ASDAX.Open_mva365 365 Day MA
1958 ASDAX.Open_mva200 200 Day MA
1963 ASDAX.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1964 ASDAX.High_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
1966 ASDAX.High_Log Log of
1967 ASDAX.High_mva365 365 Day MA
1968 ASDAX.High_mva200 200 Day MA
1973 ASDAX.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1974 ASDAX.Low_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
1976 ASDAX.Low_Log Log of
1977 ASDAX.Low_mva365 365 Day MA
1978 ASDAX.Low_mva200 200 Day MA
1983 ASDAX.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1984 ASDAX.Close_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
1986 ASDAX.Close_Log Log of
1987 ASDAX.Close_mva365 365 Day MA
1988 ASDAX.Close_mva200 200 Day MA
1990 ASDAX.Volume_YoY Year over Year
1991 ASDAX.Volume_YoY4 4 Year over 4 Year
1992 ASDAX.Volume_YoY5 5 Year over 5 Year
1993 ASDAX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1994 ASDAX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
1995 ASDAX.Volume_SmoothDer Derivative of Smoothed
1996 ASDAX.Volume_Log Log of
1997 ASDAX.Volume_mva365 365 Day MA
1998 ASDAX.Volume_mva200 200 Day MA
1999 ASDAX.Volume_mva050 50 Day MA
2003 ASDAX.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2004 ASDAX.Adjusted_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2006 ASDAX.Adjusted_Log Log of
2007 ASDAX.Adjusted_mva365 365 Day MA
2008 ASDAX.Adjusted_mva200 200 Day MA
2011 TRBUX.Open_YoY4 4 Year over 4 Year
2012 TRBUX.Open_YoY5 5 Year over 5 Year
2013 TRBUX.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2014 TRBUX.Open_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2016 TRBUX.Open_Log Log of
2017 TRBUX.Open_mva365 365 Day MA
2018 TRBUX.Open_mva200 200 Day MA
2019 TRBUX.Open_mva050 50 Day MA
2021 TRBUX.High_YoY4 4 Year over 4 Year
2022 TRBUX.High_YoY5 5 Year over 5 Year
2023 TRBUX.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2024 TRBUX.High_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2026 TRBUX.High_Log Log of
2027 TRBUX.High_mva365 365 Day MA
2028 TRBUX.High_mva200 200 Day MA
2029 TRBUX.High_mva050 50 Day MA
2031 TRBUX.Low_YoY4 4 Year over 4 Year
2032 TRBUX.Low_YoY5 5 Year over 5 Year
2033 TRBUX.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2034 TRBUX.Low_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2036 TRBUX.Low_Log Log of
2037 TRBUX.Low_mva365 365 Day MA
2038 TRBUX.Low_mva200 200 Day MA
2039 TRBUX.Low_mva050 50 Day MA
2041 TRBUX.Close_YoY4 4 Year over 4 Year
2042 TRBUX.Close_YoY5 5 Year over 5 Year
2043 TRBUX.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2044 TRBUX.Close_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2046 TRBUX.Close_Log Log of
2047 TRBUX.Close_mva365 365 Day MA
2048 TRBUX.Close_mva200 200 Day MA
2049 TRBUX.Close_mva050 50 Day MA
2050 TRBUX.Volume_YoY Year over Year
2051 TRBUX.Volume_YoY4 4 Year over 4 Year
2052 TRBUX.Volume_YoY5 5 Year over 5 Year
2053 TRBUX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2054 TRBUX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2055 TRBUX.Volume_SmoothDer Derivative of Smoothed
2056 TRBUX.Volume_Log Log of
2057 TRBUX.Volume_mva365 365 Day MA
2058 TRBUX.Volume_mva200 200 Day MA
2059 TRBUX.Volume_mva050 50 Day MA
2063 TRBUX.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2064 TRBUX.Adjusted_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2066 TRBUX.Adjusted_Log Log of
2067 TRBUX.Adjusted_mva365 365 Day MA
2068 TRBUX.Adjusted_mva200 200 Day MA
2069 TRBUX.Adjusted_mva050 50 Day MA
2110 PRVIX.Volume_YoY Year over Year
2111 PRVIX.Volume_YoY4 4 Year over 4 Year
2112 PRVIX.Volume_YoY5 5 Year over 5 Year
2113 PRVIX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2114 PRVIX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2115 PRVIX.Volume_SmoothDer Derivative of Smoothed
2116 PRVIX.Volume_Log Log of
2117 PRVIX.Volume_mva365 365 Day MA
2118 PRVIX.Volume_mva200 200 Day MA
2119 PRVIX.Volume_mva050 50 Day MA
2137 PRWCX.Open_mva365 365 Day MA
2138 PRWCX.Open_mva200 200 Day MA
2147 PRWCX.High_mva365 365 Day MA
2148 PRWCX.High_mva200 200 Day MA
2157 PRWCX.Low_mva365 365 Day MA
2158 PRWCX.Low_mva200 200 Day MA
2167 PRWCX.Close_mva365 365 Day MA
2168 PRWCX.Close_mva200 200 Day MA
2170 PRWCX.Volume_YoY Year over Year
2171 PRWCX.Volume_YoY4 4 Year over 4 Year
2172 PRWCX.Volume_YoY5 5 Year over 5 Year
2173 PRWCX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2174 PRWCX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2175 PRWCX.Volume_SmoothDer Derivative of Smoothed
2176 PRWCX.Volume_Log Log of
2177 PRWCX.Volume_mva365 365 Day MA
2178 PRWCX.Volume_mva200 200 Day MA
2179 PRWCX.Volume_mva050 50 Day MA
2187 PRWCX.Adjusted_mva365 365 Day MA
2188 PRWCX.Adjusted_mva200 200 Day MA
2230 ADOZX.Volume_YoY Year over Year
2231 ADOZX.Volume_YoY4 4 Year over 4 Year
2232 ADOZX.Volume_YoY5 5 Year over 5 Year
2233 ADOZX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2234 ADOZX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2235 ADOZX.Volume_SmoothDer Derivative of Smoothed
2236 ADOZX.Volume_Log Log of
2237 ADOZX.Volume_mva365 365 Day MA
2238 ADOZX.Volume_mva200 200 Day MA
2239 ADOZX.Volume_mva050 50 Day MA
2250 MERFX.Open_YoY Year over Year
2253 MERFX.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2254 MERFX.Open_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2255 MERFX.Open_SmoothDer Derivative of Smoothed
2256 MERFX.Open_Log Log of
2260 MERFX.High_YoY Year over Year
2263 MERFX.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2264 MERFX.High_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2265 MERFX.High_SmoothDer Derivative of Smoothed
2266 MERFX.High_Log Log of
2270 MERFX.Low_YoY Year over Year
2273 MERFX.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2274 MERFX.Low_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2275 MERFX.Low_SmoothDer Derivative of Smoothed
2276 MERFX.Low_Log Log of
2280 MERFX.Close_YoY Year over Year
2283 MERFX.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2284 MERFX.Close_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2285 MERFX.Close_SmoothDer Derivative of Smoothed
2286 MERFX.Close_Log Log of
2290 MERFX.Volume_YoY Year over Year
2291 MERFX.Volume_YoY4 4 Year over 4 Year
2292 MERFX.Volume_YoY5 5 Year over 5 Year
2293 MERFX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2294 MERFX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2295 MERFX.Volume_SmoothDer Derivative of Smoothed
2296 MERFX.Volume_Log Log of
2297 MERFX.Volume_mva365 365 Day MA
2298 MERFX.Volume_mva200 200 Day MA
2299 MERFX.Volume_mva050 50 Day MA
2300 MERFX.Adjusted_YoY Year over Year
2303 MERFX.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2304 MERFX.Adjusted_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2305 MERFX.Adjusted_SmoothDer Derivative of Smoothed
2306 MERFX.Adjusted_Log Log of
2307 MERFX.Adjusted_mva365 365 Day MA
2308 MERFX.Adjusted_mva200 200 Day MA
2312 CMNIX.Open_YoY5 5 Year over 5 Year
2314 CMNIX.Open_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2316 CMNIX.Open_Log Log of
2317 CMNIX.Open_mva365 365 Day MA
2318 CMNIX.Open_mva200 200 Day MA
2322 CMNIX.High_YoY5 5 Year over 5 Year
2324 CMNIX.High_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2326 CMNIX.High_Log Log of
2327 CMNIX.High_mva365 365 Day MA
2328 CMNIX.High_mva200 200 Day MA
2332 CMNIX.Low_YoY5 5 Year over 5 Year
2334 CMNIX.Low_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2336 CMNIX.Low_Log Log of
2337 CMNIX.Low_mva365 365 Day MA
2338 CMNIX.Low_mva200 200 Day MA
2342 CMNIX.Close_YoY5 5 Year over 5 Year
2344 CMNIX.Close_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2346 CMNIX.Close_Log Log of
2347 CMNIX.Close_mva365 365 Day MA
2348 CMNIX.Close_mva200 200 Day MA
2350 CMNIX.Volume_YoY Year over Year
2351 CMNIX.Volume_YoY4 4 Year over 4 Year
2352 CMNIX.Volume_YoY5 5 Year over 5 Year
2353 CMNIX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2354 CMNIX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2355 CMNIX.Volume_SmoothDer Derivative of Smoothed
2356 CMNIX.Volume_Log Log of
2357 CMNIX.Volume_mva365 365 Day MA
2358 CMNIX.Volume_mva200 200 Day MA
2359 CMNIX.Volume_mva050 50 Day MA
2362 CMNIX.Adjusted_YoY5 5 Year over 5 Year
2364 CMNIX.Adjusted_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2366 CMNIX.Adjusted_Log Log of
2367 CMNIX.Adjusted_mva365 365 Day MA
2368 CMNIX.Adjusted_mva200 200 Day MA
2369 CMNIX.Adjusted_mva050 50 Day MA
2372 CIHEX.Open_YoY5 5 Year over 5 Year
2377 CIHEX.Open_mva365 365 Day MA
2378 CIHEX.Open_mva200 200 Day MA
2382 CIHEX.High_YoY5 5 Year over 5 Year
2387 CIHEX.High_mva365 365 Day MA
2388 CIHEX.High_mva200 200 Day MA
2392 CIHEX.Low_YoY5 5 Year over 5 Year
2397 CIHEX.Low_mva365 365 Day MA
2398 CIHEX.Low_mva200 200 Day MA
2402 CIHEX.Close_YoY5 5 Year over 5 Year
2407 CIHEX.Close_mva365 365 Day MA
2408 CIHEX.Close_mva200 200 Day MA
2410 CIHEX.Volume_YoY Year over Year
2411 CIHEX.Volume_YoY4 4 Year over 4 Year
2412 CIHEX.Volume_YoY5 5 Year over 5 Year
2413 CIHEX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2414 CIHEX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2415 CIHEX.Volume_SmoothDer Derivative of Smoothed
2416 CIHEX.Volume_Log Log of
2417 CIHEX.Volume_mva365 365 Day MA
2418 CIHEX.Volume_mva200 200 Day MA
2419 CIHEX.Volume_mva050 50 Day MA
2422 CIHEX.Adjusted_YoY5 5 Year over 5 Year
2427 CIHEX.Adjusted_mva365 365 Day MA
2428 CIHEX.Adjusted_mva200 200 Day MA
2431 IMPCH_YoY4 U.S. Imports of Goods by Customs Basis from China (Monthly, NSA) 4 Year over 4 Year
2432 IMPCH_YoY5 U.S. Imports of Goods by Customs Basis from China (Monthly, NSA) 5 Year over 5 Year
2436 IMPCH_Log Log of U.S. Imports of Goods by Customs Basis from China (Monthly, NSA)
2438 IMPCH_mva200 U.S. Imports of Goods by Customs Basis from China (Monthly, NSA) 200 Day MA
2439 IMPCH_mva050 U.S. Imports of Goods by Customs Basis from China (Monthly, NSA) 50 Day MA
2443 EXPCH_Smooth Savitsky-Golay Smoothed (p=3, n=365) U.S. Exports of Goods by F.A.S. Basis to China, Mainland (Monthly, NSA)
2445 EXPCH_SmoothDer Derivative of Smoothed U.S. Exports of Goods by F.A.S. Basis to China, Mainland (Monthly, NSA)
2446 EXPCH_Log Log of U.S. Exports of Goods by F.A.S. Basis to China, Mainland (Monthly, NSA)
2449 EXPCH_mva050 U.S. Exports of Goods by F.A.S. Basis to China, Mainland (Monthly, NSA) 50 Day MA
2450 IMPMX_YoY U.S. Imports of Goods by Customs Basis from Mexico (Monthly, NSA) Year over Year
2451 IMPMX_YoY4 U.S. Imports of Goods by Customs Basis from Mexico (Monthly, NSA) 4 Year over 4 Year
2452 IMPMX_YoY5 U.S. Imports of Goods by Customs Basis from Mexico (Monthly, NSA) 5 Year over 5 Year
2457 IMPMX_mva365 U.S. Imports of Goods by Customs Basis from Mexico (Monthly, NSA) 365 Day MA
2460 EXPMX_YoY U.S. Exports of Goods by F.A.S. Basis to Mexico (Monthly, NSA) Year over Year
2461 EXPMX_YoY4 U.S. Exports of Goods by F.A.S. Basis to Mexico (Monthly, NSA) 4 Year over 4 Year
2462 EXPMX_YoY5 U.S. Exports of Goods by F.A.S. Basis to Mexico (Monthly, NSA) 5 Year over 5 Year
2468 EXPMX_mva200 U.S. Exports of Goods by F.A.S. Basis to Mexico (Monthly, NSA) 200 Day MA
2471 HSN1FNSA_YoY4 New One Family Houses Sold: United States (Monthly, NSA) 4 Year over 4 Year
2472 HSN1FNSA_YoY5 New One Family Houses Sold: United States (Monthly, NSA) 5 Year over 5 Year
2473 HSN1FNSA_Smooth Savitsky-Golay Smoothed (p=3, n=365) New One Family Houses Sold: United States (Monthly, NSA)
2477 HSN1FNSA_mva365 New One Family Houses Sold: United States (Monthly, NSA) 365 Day MA
2480 HNFSUSNSA_YoY New One Family Houses for Sale in the United States (Monthly, NSA) Year over Year
2485 HNFSUSNSA_SmoothDer Derivative of Smoothed New One Family Houses for Sale in the United States (Monthly, NSA)
2486 HNFSUSNSA_Log Log of New One Family Houses for Sale in the United States (Monthly, NSA)
2488 HNFSUSNSA_mva200 New One Family Houses for Sale in the United States (Monthly, NSA) 200 Day MA
2489 HNFSUSNSA_mva050 New One Family Houses for Sale in the United States (Monthly, NSA) 50 Day MA
2493 BUSLOANS_Smooth Savitsky-Golay Smoothed (p=3, n=365) Commercial and Industrial Loans, All Commercial Banks (Monthly, SA)
2495 BUSLOANS_SmoothDer Derivative of Smoothed Commercial and Industrial Loans, All Commercial Banks (Monthly, SA)
2496 BUSLOANS_Log Log of Commercial and Industrial Loans, All Commercial Banks (Monthly, SA)
2499 BUSLOANS_mva050 Commercial and Industrial Loans, All Commercial Banks (Monthly, SA) 50 Day MA
2503 TOTCI_Smooth Savitsky-Golay Smoothed (p=3, n=365) Commercial and Industrial Loans, All Commercial Banks (Weekly, SA)
2505 TOTCI_SmoothDer Derivative of Smoothed Commercial and Industrial Loans, All Commercial Banks (Weekly, SA)
2515 BUSLOANSNSA_SmoothDer Derivative of Smoothed Commercial and Industrial Loans, All Commercial Banks (Monthly, NSA)
2523 REALLNNSA_Smooth Savitsky-Golay Smoothed (p=3, n=365) Real Estate Loans, All Commercial Banks (Monthly, NSA)
2525 REALLNNSA_SmoothDer Derivative of Smoothed Real Estate Loans, All Commercial Banks (Monthly, NSA)
2526 REALLNNSA_Log Log of Real Estate Loans, All Commercial Banks (Monthly, NSA)
2527 REALLNNSA_mva365 Real Estate Loans, All Commercial Banks (Monthly, NSA) 365 Day MA
2528 REALLNNSA_mva200 Real Estate Loans, All Commercial Banks (Monthly, NSA) 200 Day MA
2529 REALLNNSA_mva050 Real Estate Loans, All Commercial Banks (Monthly, NSA) 50 Day MA
2533 REALLN_Smooth Savitsky-Golay Smoothed (p=3, n=365) Real Estate Loans, All Commercial Banks (Monthly, SA)
2536 REALLN_Log Log of Real Estate Loans, All Commercial Banks (Monthly, SA)
2537 REALLN_mva365 Real Estate Loans, All Commercial Banks (Monthly, SA) 365 Day MA
2538 REALLN_mva200 Real Estate Loans, All Commercial Banks (Monthly, SA) 200 Day MA
2539 REALLN_mva050 Real Estate Loans, All Commercial Banks (Monthly, SA) 50 Day MA
2543 RELACBW027NBOG_Smooth Savitsky-Golay Smoothed (p=3, n=365) Real Estate Loans, All Commercial Banks (Weekly, NSA)
2545 RELACBW027NBOG_SmoothDer Derivative of Smoothed Real Estate Loans, All Commercial Banks (Weekly, NSA)
2546 RELACBW027NBOG_Log Log of Real Estate Loans, All Commercial Banks (Weekly, NSA)
2547 RELACBW027NBOG_mva365 Real Estate Loans, All Commercial Banks (Weekly, NSA) 365 Day MA
2548 RELACBW027NBOG_mva200 Real Estate Loans, All Commercial Banks (Weekly, NSA) 200 Day MA
2549 RELACBW027NBOG_mva050 Real Estate Loans, All Commercial Banks (Weekly, NSA) 50 Day MA
2553 RELACBW027SBOG_Smooth Savitsky-Golay Smoothed (p=3, n=365) Real Estate Loans, All Commercial Banks (Weekly, SA)
2557 RELACBW027SBOG_mva365 Real Estate Loans, All Commercial Banks (Weekly, SA) 365 Day MA
2558 RELACBW027SBOG_mva200 Real Estate Loans, All Commercial Banks (Weekly, SA) 200 Day MA
2559 RELACBW027SBOG_mva050 Real Estate Loans, All Commercial Banks (Weekly, SA) 50 Day MA
2563 RREACBM027NBOG_Smooth Savitsky-Golay Smoothed (p=3, n=365) Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Monthly, NSA)
2565 RREACBM027NBOG_SmoothDer Derivative of Smoothed Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Monthly, NSA)
2566 RREACBM027NBOG_Log Log of Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Monthly, NSA)
2567 RREACBM027NBOG_mva365 Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Monthly, NSA) 365 Day MA
2568 RREACBM027NBOG_mva200 Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Monthly, NSA) 200 Day MA
2569 RREACBM027NBOG_mva050 Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Monthly, NSA) 50 Day MA
2573 RREACBM027SBOG_Smooth Savitsky-Golay Smoothed (p=3, n=365) Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Monthly, SA)
2577 RREACBM027SBOG_mva365 Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Monthly, SA) 365 Day MA
2578 RREACBM027SBOG_mva200 Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Monthly, SA) 200 Day MA
2583 RREACBW027SBOG_Smooth Savitsky-Golay Smoothed (p=3, n=365) Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Weekly, SA)
2587 RREACBW027SBOG_mva365 Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Weekly, SA) 365 Day MA
2588 RREACBW027SBOG_mva200 Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Weekly, SA) 200 Day MA
2593 RREACBW027NBOG_Smooth Savitsky-Golay Smoothed (p=3, n=365) Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Weekly, NSA)
2595 RREACBW027NBOG_SmoothDer Derivative of Smoothed Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Weekly, NSA)
2596 RREACBW027NBOG_Log Log of Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Weekly, NSA)
2597 RREACBW027NBOG_mva365 Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Weekly, NSA) 365 Day MA
2598 RREACBW027NBOG_mva200 Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Weekly, NSA) 200 Day MA
2599 RREACBW027NBOG_mva050 Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Weekly, NSA) 50 Day MA
2603 MORTGAGE30US_Smooth Savitsky-Golay Smoothed (p=3, n=365) 30-Year Fixed Rate Mortgage Average in the United States
2605 MORTGAGE30US_SmoothDer Derivative of Smoothed 30-Year Fixed Rate Mortgage Average in the United States
2607 MORTGAGE30US_mva365 30-Year Fixed Rate Mortgage Average in the United States 365 Day MA
2608 MORTGAGE30US_mva200 30-Year Fixed Rate Mortgage Average in the United States 200 Day MA
2609 MORTGAGE30US_mva050 30-Year Fixed Rate Mortgage Average in the United States 50 Day MA
2615 CONSUMERNSA_SmoothDer Derivative of Smoothed Consumer Loans, All Commercial Banks
2616 CONSUMERNSA_Log Log of Consumer Loans, All Commercial Banks
2617 CONSUMERNSA_mva365 Consumer Loans, All Commercial Banks 365 Day MA
2618 CONSUMERNSA_mva200 Consumer Loans, All Commercial Banks 200 Day MA
2619 CONSUMERNSA_mva050 Consumer Loans, All Commercial Banks 50 Day MA
2623 TOTLLNSA_Smooth Savitsky-Golay Smoothed (p=3, n=365) Loans and Leases in Bank Credit, All Commercial Banks
2625 TOTLLNSA_SmoothDer Derivative of Smoothed Loans and Leases in Bank Credit, All Commercial Banks
2627 TOTLLNSA_mva365 Loans and Leases in Bank Credit, All Commercial Banks 365 Day MA
2628 TOTLLNSA_mva200 Loans and Leases in Bank Credit, All Commercial Banks 200 Day MA
2629 TOTLLNSA_mva050 Loans and Leases in Bank Credit, All Commercial Banks 50 Day MA
2633 DPSACBW027SBOG_Smooth Savitsky-Golay Smoothed (p=3, n=365) Deposits, All Commercial Banks
2635 DPSACBW027SBOG_SmoothDer Derivative of Smoothed Deposits, All Commercial Banks
2646 DRCLACBS_Log Log of Delinquency Rate on Consumer Loans, All Commercial Banks, SA
2647 DRCLACBS_mva365 Delinquency Rate on Consumer Loans, All Commercial Banks, SA 365 Day MA
2648 DRCLACBS_mva200 Delinquency Rate on Consumer Loans, All Commercial Banks, SA 200 Day MA
2649 DRCLACBS_mva050 Delinquency Rate on Consumer Loans, All Commercial Banks, SA 50 Day MA
2663 SRPSABSNNCB_Smooth Savitsky-Golay Smoothed (p=3, n=365) Nonfinancial corporate business; security repurchase agreements; asset, Level (NSA)
2665 SRPSABSNNCB_SmoothDer Derivative of Smoothed Nonfinancial corporate business; security repurchase agreements; asset, Level (NSA)
2666 SRPSABSNNCB_Log Log of Nonfinancial corporate business; security repurchase agreements; asset, Level (NSA)
2669 SRPSABSNNCB_mva050 Nonfinancial corporate business; security repurchase agreements; asset, Level (NSA) 50 Day MA
2673 ASTLL_Smooth Savitsky-Golay Smoothed (p=3, n=365) All sectors; total loans; liability, Level (NSA)
2675 ASTLL_SmoothDer Derivative of Smoothed All sectors; total loans; liability, Level (NSA)
2676 ASTLL_Log Log of All sectors; total loans; liability, Level (NSA)
2677 ASTLL_mva365 All sectors; total loans; liability, Level (NSA) 365 Day MA
2679 ASTLL_mva050 All sectors; total loans; liability, Level (NSA) 50 Day MA
2683 FBDILNECA_Smooth Savitsky-Golay Smoothed (p=3, n=365) Domestic financial sectors; depository institution loans n.e.c.; asset, Level (NSA)
2685 FBDILNECA_SmoothDer Derivative of Smoothed Domestic financial sectors; depository institution loans n.e.c.; asset, Level (NSA)
2686 FBDILNECA_Log Log of Domestic financial sectors; depository institution loans n.e.c.; asset, Level (NSA)
2689 FBDILNECA_mva050 Domestic financial sectors; depository institution loans n.e.c.; asset, Level (NSA) 50 Day MA
2693 ASOLAL_Smooth Savitsky-Golay Smoothed (p=3, n=365) All sectors; other loans and advances; liability, Level (NSA)
2695 ASOLAL_SmoothDer Derivative of Smoothed All sectors; other loans and advances; liability, Level (NSA)
2696 ASOLAL_Log Log of All sectors; other loans and advances; liability, Level (NSA)
2699 ASOLAL_mva050 All sectors; other loans and advances; liability, Level (NSA) 50 Day MA
2706 ASTMA_Log Log of All sectors; total mortgages; asset, Level (NSA)
2707 ASTMA_mva365 All sectors; total mortgages; asset, Level (NSA) 365 Day MA
2708 ASTMA_mva200 All sectors; total mortgages; asset, Level (NSA) 200 Day MA
2709 ASTMA_mva050 All sectors; total mortgages; asset, Level (NSA) 50 Day MA
2716 ASHMA_Log Log of All sectors; home mortgages; asset, Level (NSA)
2717 ASHMA_mva365 All sectors; home mortgages; asset, Level (NSA) 365 Day MA
2718 ASHMA_mva200 All sectors; home mortgages; asset, Level (NSA) 200 Day MA
2719 ASHMA_mva050 All sectors; home mortgages; asset, Level (NSA) 50 Day MA
2726 ASMRMA_Log Log of All sectors; multifamily residential mortgages; asset, Level (NSA)
2727 ASMRMA_mva365 All sectors; multifamily residential mortgages; asset, Level (NSA) 365 Day MA
2728 ASMRMA_mva200 All sectors; multifamily residential mortgages; asset, Level (NSA) 200 Day MA
2729 ASMRMA_mva050 All sectors; multifamily residential mortgages; asset, Level (NSA) 50 Day MA
2733 ASCMA_Smooth Savitsky-Golay Smoothed (p=3, n=365) All sectors; commercial mortgages; asset, Level (NSA)
2736 ASCMA_Log Log of All sectors; commercial mortgages; asset, Level (NSA)
2737 ASCMA_mva365 All sectors; commercial mortgages; asset, Level (NSA) 365 Day MA
2738 ASCMA_mva200 All sectors; commercial mortgages; asset, Level (NSA) 200 Day MA
2739 ASCMA_mva050 All sectors; commercial mortgages; asset, Level (NSA) 50 Day MA
2746 ASFMA_Log Log of All sectors; farm mortgages; asset, Level (NSA)
2747 ASFMA_mva365 All sectors; farm mortgages; asset, Level (NSA) 365 Day MA
2748 ASFMA_mva200 All sectors; farm mortgages; asset, Level (NSA) 200 Day MA
2749 ASFMA_mva050 All sectors; farm mortgages; asset, Level (NSA) 50 Day MA
2756 CCLBSHNO_Log Log of Households and nonprofit organizations; consumer credit; liability, Level (NSA)
2757 CCLBSHNO_mva365 Households and nonprofit organizations; consumer credit; liability, Level (NSA) 365 Day MA
2758 CCLBSHNO_mva200 Households and nonprofit organizations; consumer credit; liability, Level (NSA) 200 Day MA
2759 CCLBSHNO_mva050 Households and nonprofit organizations; consumer credit; liability, Level (NSA) 50 Day MA
2763 FBDSILQ027S_Smooth Savitsky-Golay Smoothed (p=3, n=365) Domestic financial sectors debt securities; liability, Level (NSA)
2765 FBDSILQ027S_SmoothDer Derivative of Smoothed Domestic financial sectors debt securities; liability, Level (NSA)
2766 FBDSILQ027S_Log Log of Domestic financial sectors debt securities; liability, Level (NSA)
2767 FBDSILQ027S_mva365 Domestic financial sectors debt securities; liability, Level (NSA) 365 Day MA
2769 FBDSILQ027S_mva050 Domestic financial sectors debt securities; liability, Level (NSA) 50 Day MA
2772 FBLL_YoY5 Domestic financial sectors loans; liability, Level (NSA) 5 Year over 5 Year
2773 FBLL_Smooth Savitsky-Golay Smoothed (p=3, n=365) Domestic financial sectors loans; liability, Level (NSA)
2775 FBLL_SmoothDer Derivative of Smoothed Domestic financial sectors loans; liability, Level (NSA)
2776 FBLL_Log Log of Domestic financial sectors loans; liability, Level (NSA)
2779 FBLL_mva050 Domestic financial sectors loans; liability, Level (NSA) 50 Day MA
2783 NCBDBIQ027S_Smooth Savitsky-Golay Smoothed (p=3, n=365) Nonfinancial corporate business; debt securities; liability, Level
2786 NCBDBIQ027S_Log Log of Nonfinancial corporate business; debt securities; liability, Level
2787 NCBDBIQ027S_mva365 Nonfinancial corporate business; debt securities; liability, Level 365 Day MA
2788 NCBDBIQ027S_mva200 Nonfinancial corporate business; debt securities; liability, Level 200 Day MA
2789 NCBDBIQ027S_mva050 Nonfinancial corporate business; debt securities; liability, Level 50 Day MA
2793 DGS10_Smooth Savitsky-Golay Smoothed (p=3, n=365) 10-Year Treasury Constant Maturity Rate
2795 DGS10_SmoothDer Derivative of Smoothed 10-Year Treasury Constant Maturity Rate
2797 DGS10_mva365 10-Year Treasury Constant Maturity Rate 365 Day MA
2798 DGS10_mva200 10-Year Treasury Constant Maturity Rate 200 Day MA
2803 TNX.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2805 TNX.Open_SmoothDer Derivative of Smoothed
2807 TNX.Open_mva365 365 Day MA
2808 TNX.Open_mva200 200 Day MA
2813 TNX.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2815 TNX.High_SmoothDer Derivative of Smoothed
2817 TNX.High_mva365 365 Day MA
2818 TNX.High_mva200 200 Day MA
2823 TNX.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2825 TNX.Low_SmoothDer Derivative of Smoothed
2827 TNX.Low_mva365 365 Day MA
2828 TNX.Low_mva200 200 Day MA
2833 TNX.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2835 TNX.Close_SmoothDer Derivative of Smoothed
2837 TNX.Close_mva365 365 Day MA
2838 TNX.Close_mva200 200 Day MA
2840 TNX.Volume_YoY Year over Year
2841 TNX.Volume_YoY4 4 Year over 4 Year
2842 TNX.Volume_YoY5 5 Year over 5 Year
2843 TNX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2844 TNX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2845 TNX.Volume_SmoothDer Derivative of Smoothed
2846 TNX.Volume_Log Log of
2847 TNX.Volume_mva365 365 Day MA
2848 TNX.Volume_mva200 200 Day MA
2849 TNX.Volume_mva050 50 Day MA
2853 TNX.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2855 TNX.Adjusted_SmoothDer Derivative of Smoothed
2857 TNX.Adjusted_mva365 365 Day MA
2858 TNX.Adjusted_mva200 200 Day MA
2862 CLF.Open_YoY5 5 Year over 5 Year
2863 CLF.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2865 CLF.Open_SmoothDer Derivative of Smoothed
2866 CLF.Open_Log Log of
2868 CLF.Open_mva200 200 Day MA
2872 CLF.High_YoY5 5 Year over 5 Year
2873 CLF.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2875 CLF.High_SmoothDer Derivative of Smoothed
2878 CLF.High_mva200 200 Day MA
2882 CLF.Low_YoY5 5 Year over 5 Year
2883 CLF.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2885 CLF.Low_SmoothDer Derivative of Smoothed
2886 CLF.Low_Log Log of
2888 CLF.Low_mva200 200 Day MA
2892 CLF.Close_YoY5 5 Year over 5 Year
2893 CLF.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2895 CLF.Close_SmoothDer Derivative of Smoothed
2896 CLF.Close_Log Log of
2898 CLF.Close_mva200 200 Day MA
2906 CLF.Volume_Log Log of
2912 CLF.Adjusted_YoY5 5 Year over 5 Year
2913 CLF.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2915 CLF.Adjusted_SmoothDer Derivative of Smoothed
2916 CLF.Adjusted_Log Log of
2918 CLF.Adjusted_mva200 200 Day MA
2923 DGS30_Smooth Savitsky-Golay Smoothed (p=3, n=365) 10-Year Treasury Constant Maturity Rate
2925 DGS30_SmoothDer Derivative of Smoothed 10-Year Treasury Constant Maturity Rate
2927 DGS30_mva365 10-Year Treasury Constant Maturity Rate 365 Day MA
2928 DGS30_mva200 10-Year Treasury Constant Maturity Rate 200 Day MA
2935 DGS1_SmoothDer Derivative of Smoothed 1-Year Treasury Constant Maturity Rate
2937 DGS1_mva365 1-Year Treasury Constant Maturity Rate 365 Day MA
2938 DGS1_mva200 1-Year Treasury Constant Maturity Rate 200 Day MA
2945 DGS2_SmoothDer Derivative of Smoothed 2-Year Treasury Constant Maturity Rate
2947 DGS2_mva365 2-Year Treasury Constant Maturity Rate 365 Day MA
2948 DGS2_mva200 2-Year Treasury Constant Maturity Rate 200 Day MA
2951 TB3MS_YoY4 3-Month Treasury Bill: Secondary Market Rate (Monthly) 4 Year over 4 Year
2956 TB3MS_Log Log of 3-Month Treasury Bill: Secondary Market Rate (Monthly)
2957 TB3MS_mva365 3-Month Treasury Bill: Secondary Market Rate (Monthly) 365 Day MA
2958 TB3MS_mva200 3-Month Treasury Bill: Secondary Market Rate (Monthly) 200 Day MA
2959 TB3MS_mva050 3-Month Treasury Bill: Secondary Market Rate (Monthly) 50 Day MA
2966 DTB3_Log Log of 3-Month Treasury Bill: Secondary Market Rate (Daily)
2967 DTB3_mva365 3-Month Treasury Bill: Secondary Market Rate (Daily) 365 Day MA
2968 DTB3_mva200 3-Month Treasury Bill: Secondary Market Rate (Daily) 200 Day MA
2976 IRX.Open_Log Log of
2977 IRX.Open_mva365 365 Day MA
2978 IRX.Open_mva200 200 Day MA
2986 IRX.High_Log Log of
2987 IRX.High_mva365 365 Day MA
2988 IRX.High_mva200 200 Day MA
2996 IRX.Low_Log Log of
2997 IRX.Low_mva365 365 Day MA
2998 IRX.Low_mva200 200 Day MA
3006 IRX.Close_Log Log of
3007 IRX.Close_mva365 365 Day MA
3008 IRX.Close_mva200 200 Day MA
3010 IRX.Volume_YoY Year over Year
3011 IRX.Volume_YoY4 4 Year over 4 Year
3012 IRX.Volume_YoY5 5 Year over 5 Year
3013 IRX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3014 IRX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
3015 IRX.Volume_SmoothDer Derivative of Smoothed
3016 IRX.Volume_Log Log of
3017 IRX.Volume_mva365 365 Day MA
3018 IRX.Volume_mva200 200 Day MA
3019 IRX.Volume_mva050 50 Day MA
3026 IRX.Adjusted_Log Log of
3027 IRX.Adjusted_mva365 365 Day MA
3028 IRX.Adjusted_mva200 200 Day MA
3033 DCOILWTICO_Smooth Savitsky-Golay Smoothed (p=3, n=365) Crude Oil Prices: West Texas Intermediate (WTI) Cushing, Oklahoma
3035 DCOILWTICO_SmoothDer Derivative of Smoothed Crude Oil Prices: West Texas Intermediate (WTI) Cushing, Oklahoma
3036 DCOILWTICO_Log Log of Crude Oil Prices: West Texas Intermediate (WTI) Cushing, Oklahoma
3038 DCOILWTICO_mva200 Crude Oil Prices: West Texas Intermediate (WTI) Cushing, Oklahoma 200 Day MA
3042 DCOILBRENTEU_YoY5 Crude Oil Prices: Brent - Europe 5 Year over 5 Year
3043 DCOILBRENTEU_Smooth Savitsky-Golay Smoothed (p=3, n=365) Crude Oil Prices: Brent - Europe
3045 DCOILBRENTEU_SmoothDer Derivative of Smoothed Crude Oil Prices: Brent - Europe
3048 DCOILBRENTEU_mva200 Crude Oil Prices: Brent - Europe 200 Day MA
3051 NEWORDER_YoY4 Manufacturers’ New Orders: Nondefense Capital Goods Excluding Aircraft 4 Year over 4 Year
3052 NEWORDER_YoY5 Manufacturers’ New Orders: Nondefense Capital Goods Excluding Aircraft 5 Year over 5 Year
3053 NEWORDER_Smooth Savitsky-Golay Smoothed (p=3, n=365) Manufacturers’ New Orders: Nondefense Capital Goods Excluding Aircraft
3057 NEWORDER_mva365 Manufacturers’ New Orders: Nondefense Capital Goods Excluding Aircraft 365 Day MA
3067 ALTSALES_mva365 Light Weight Vehicle Sales: Autos and Light Trucks 365 Day MA
3082 GSPC.Open_YoY5 5 Year over 5 Year
3087 GSPC.Open_mva365 365 Day MA
3088 GSPC.Open_mva200 200 Day MA
3092 GSPC.High_YoY5 5 Year over 5 Year
3097 GSPC.High_mva365 365 Day MA
3098 GSPC.High_mva200 200 Day MA
3102 GSPC.Low_YoY5 5 Year over 5 Year
3107 GSPC.Low_mva365 365 Day MA
3108 GSPC.Low_mva200 200 Day MA
3112 GSPC.Close_YoY5 5 Year over 5 Year
3117 GSPC.Close_mva365 365 Day MA
3118 GSPC.Close_mva200 200 Day MA
3125 GSPC.Volume_SmoothDer Derivative of Smoothed
3126 GSPC.Volume_Log Log of
3132 GSPC.Adjusted_YoY5 5 Year over 5 Year
3137 GSPC.Adjusted_mva365 365 Day MA
3138 GSPC.Adjusted_mva200 200 Day MA
3142 FXAIX.Open_YoY5 5 Year over 5 Year
3147 FXAIX.Open_mva365 365 Day MA
3148 FXAIX.Open_mva200 200 Day MA
3152 FXAIX.High_YoY5 5 Year over 5 Year
3157 FXAIX.High_mva365 365 Day MA
3158 FXAIX.High_mva200 200 Day MA
3162 FXAIX.Low_YoY5 5 Year over 5 Year
3167 FXAIX.Low_mva365 365 Day MA
3168 FXAIX.Low_mva200 200 Day MA
3172 FXAIX.Close_YoY5 5 Year over 5 Year
3177 FXAIX.Close_mva365 365 Day MA
3178 FXAIX.Close_mva200 200 Day MA
3180 FXAIX.Volume_YoY Year over Year
3181 FXAIX.Volume_YoY4 4 Year over 4 Year
3182 FXAIX.Volume_YoY5 5 Year over 5 Year
3183 FXAIX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3184 FXAIX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
3185 FXAIX.Volume_SmoothDer Derivative of Smoothed
3186 FXAIX.Volume_Log Log of
3187 FXAIX.Volume_mva365 365 Day MA
3188 FXAIX.Volume_mva200 200 Day MA
3189 FXAIX.Volume_mva050 50 Day MA
3192 FXAIX.Adjusted_YoY5 5 Year over 5 Year
3197 FXAIX.Adjusted_mva365 365 Day MA
3198 FXAIX.Adjusted_mva200 200 Day MA
3207 FTIHX.Open_mva365 365 Day MA
3217 FTIHX.High_mva365 365 Day MA
3227 FTIHX.Low_mva365 365 Day MA
3237 FTIHX.Close_mva365 365 Day MA
3240 FTIHX.Volume_YoY Year over Year
3241 FTIHX.Volume_YoY4 4 Year over 4 Year
3242 FTIHX.Volume_YoY5 5 Year over 5 Year
3243 FTIHX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3244 FTIHX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
3245 FTIHX.Volume_SmoothDer Derivative of Smoothed
3246 FTIHX.Volume_Log Log of
3247 FTIHX.Volume_mva365 365 Day MA
3248 FTIHX.Volume_mva200 200 Day MA
3249 FTIHX.Volume_mva050 50 Day MA
3257 FTIHX.Adjusted_mva365 365 Day MA
3267 MDIZX.Open_mva365 365 Day MA
3277 MDIZX.High_mva365 365 Day MA
3287 MDIZX.Low_mva365 365 Day MA
3297 MDIZX.Close_mva365 365 Day MA
3300 MDIZX.Volume_YoY Year over Year
3301 MDIZX.Volume_YoY4 4 Year over 4 Year
3302 MDIZX.Volume_YoY5 5 Year over 5 Year
3303 MDIZX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3304 MDIZX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
3305 MDIZX.Volume_SmoothDer Derivative of Smoothed
3306 MDIZX.Volume_Log Log of
3307 MDIZX.Volume_mva365 365 Day MA
3308 MDIZX.Volume_mva200 200 Day MA
3309 MDIZX.Volume_mva050 50 Day MA
3317 MDIZX.Adjusted_mva365 365 Day MA
3360 DODIX.Volume_YoY Year over Year
3361 DODIX.Volume_YoY4 4 Year over 4 Year
3362 DODIX.Volume_YoY5 5 Year over 5 Year
3363 DODIX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3364 DODIX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
3365 DODIX.Volume_SmoothDer Derivative of Smoothed
3366 DODIX.Volume_Log Log of
3367 DODIX.Volume_mva365 365 Day MA
3368 DODIX.Volume_mva200 200 Day MA
3369 DODIX.Volume_mva050 50 Day MA
3377 DODIX.Adjusted_mva365 365 Day MA
3382 RLG.Open_YoY5 5 Year over 5 Year
3386 RLG.Open_Log Log of
3387 RLG.Open_mva365 365 Day MA
3388 RLG.Open_mva200 200 Day MA
3392 RLG.High_YoY5 5 Year over 5 Year
3397 RLG.High_mva365 365 Day MA
3398 RLG.High_mva200 200 Day MA
3406 RLG.Low_Log Log of
3407 RLG.Low_mva365 365 Day MA
3408 RLG.Low_mva200 200 Day MA
3417 RLG.Close_mva365 365 Day MA
3418 RLG.Close_mva200 200 Day MA
3420 RLG.Volume_YoY Year over Year
3421 RLG.Volume_YoY4 4 Year over 4 Year
3422 RLG.Volume_YoY5 5 Year over 5 Year
3423 RLG.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3424 RLG.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
3425 RLG.Volume_SmoothDer Derivative of Smoothed
3426 RLG.Volume_Log Log of
3427 RLG.Volume_mva365 365 Day MA
3428 RLG.Volume_mva200 200 Day MA
3429 RLG.Volume_mva050 50 Day MA
3437 RLG.Adjusted_mva365 365 Day MA
3438 RLG.Adjusted_mva200 200 Day MA
3442 DJI.Open_YoY5 5 Year over 5 Year
3447 DJI.Open_mva365 365 Day MA
3448 DJI.Open_mva200 200 Day MA
3452 DJI.High_YoY5 5 Year over 5 Year
3457 DJI.High_mva365 365 Day MA
3458 DJI.High_mva200 200 Day MA
3462 DJI.Low_YoY5 5 Year over 5 Year
3467 DJI.Low_mva365 365 Day MA
3468 DJI.Low_mva200 200 Day MA
3472 DJI.Close_YoY5 5 Year over 5 Year
3477 DJI.Close_mva365 365 Day MA
3478 DJI.Close_mva200 200 Day MA
3485 DJI.Volume_SmoothDer Derivative of Smoothed
3492 DJI.Adjusted_YoY5 5 Year over 5 Year
3497 DJI.Adjusted_mva365 365 Day MA
3498 DJI.Adjusted_mva200 200 Day MA
3507 STOXX50E.Open_mva365 365 Day MA
3512 STOXX50E.High_YoY5 5 Year over 5 Year
3517 STOXX50E.High_mva365 365 Day MA
3527 STOXX50E.Low_mva365 365 Day MA
3537 STOXX50E.Close_mva365 365 Day MA
3543 STOXX50E.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3545 STOXX50E.Volume_SmoothDer Derivative of Smoothed
3546 STOXX50E.Volume_Log Log of
3557 STOXX50E.Adjusted_mva365 365 Day MA
3562 EFA.Open_YoY5 5 Year over 5 Year
3567 EFA.Open_mva365 365 Day MA
3577 EFA.High_mva365 365 Day MA
3587 EFA.Low_mva365 365 Day MA
3597 EFA.Close_mva365 365 Day MA
3603 EFA.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3605 EFA.Volume_SmoothDer Derivative of Smoothed
3617 EFA.Adjusted_mva365 365 Day MA
3626 GDP_Log Log of Gross Domestic Product
3627 GDP_mva365 Gross Domestic Product 365 Day MA
3628 GDP_mva200 Gross Domestic Product 200 Day MA
3629 GDP_mva050 Gross Domestic Product 50 Day MA
3636 FNDEFX_Log Log of Federal Government: Nondefense Consumption Expenditures and Gross Investment (SA, Annual Rate)
3637 FNDEFX_mva365 Federal Government: Nondefense Consumption Expenditures and Gross Investment (SA, Annual Rate) 365 Day MA
3638 FNDEFX_mva200 Federal Government: Nondefense Consumption Expenditures and Gross Investment (SA, Annual Rate) 200 Day MA
3639 FNDEFX_mva050 Federal Government: Nondefense Consumption Expenditures and Gross Investment (SA, Annual Rate) 50 Day MA
3646 FDEFX_Log Log of Federal Government: National Defense Consumption Expenditures and Gross Investment (SA, Annual Rate)
3647 FDEFX_mva365 Federal Government: National Defense Consumption Expenditures and Gross Investment (SA, Annual Rate) 365 Day MA
3648 FDEFX_mva200 Federal Government: National Defense Consumption Expenditures and Gross Investment (SA, Annual Rate) 200 Day MA
3649 FDEFX_mva050 Federal Government: National Defense Consumption Expenditures and Gross Investment (SA, Annual Rate) 50 Day MA
3651 GDPNOW_YoY4 Fed Atlanta GDPNow 4 Year over 4 Year
3656 GDPNOW_Log Log of Fed Atlanta GDPNow
3661 GDPC1_YoY4 Real Gross Domestic Product 4 Year over 4 Year
3666 GDPC1_Log Log of Real Gross Domestic Product
3667 GDPC1_mva365 Real Gross Domestic Product 365 Day MA
3668 GDPC1_mva200 Real Gross Domestic Product 200 Day MA
3669 GDPC1_mva050 Real Gross Domestic Product 50 Day MA
3676 GDPDEF_Log Log of Gross Domestic Product: Implicit Price Deflator
3677 GDPDEF_mva365 Gross Domestic Product: Implicit Price Deflator 365 Day MA
3678 GDPDEF_mva200 Gross Domestic Product: Implicit Price Deflator 200 Day MA
3679 GDPDEF_mva050 Gross Domestic Product: Implicit Price Deflator 50 Day MA
3687 VIG.Open_mva365 365 Day MA
3688 VIG.Open_mva200 200 Day MA
3697 VIG.High_mva365 365 Day MA
3698 VIG.High_mva200 200 Day MA
3707 VIG.Low_mva365 365 Day MA
3708 VIG.Low_mva200 200 Day MA
3717 VIG.Close_mva365 365 Day MA
3718 VIG.Close_mva200 200 Day MA
3723 VIG.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3725 VIG.Volume_SmoothDer Derivative of Smoothed
3737 VIG.Adjusted_mva365 365 Day MA
3738 VIG.Adjusted_mva200 200 Day MA
3751 FEDFUNDS_YoY4 Effective Federal Funds Rate 4 Year over 4 Year
3756 FEDFUNDS_Log Log of Effective Federal Funds Rate
3757 FEDFUNDS_mva365 Effective Federal Funds Rate 365 Day MA
3758 FEDFUNDS_mva200 Effective Federal Funds Rate 200 Day MA
3759 FEDFUNDS_mva050 Effective Federal Funds Rate 50 Day MA
3761 GPDI_YoY4 Gross Private Domestic Investment 4 Year over 4 Year
3766 GPDI_Log Log of Gross Private Domestic Investment
3767 GPDI_mva365 Gross Private Domestic Investment 365 Day MA
3768 GPDI_mva200 Gross Private Domestic Investment 200 Day MA
3769 GPDI_mva050 Gross Private Domestic Investment 50 Day MA
3771 W790RC1Q027SBEA_YoY4 Net domestic investment: Private: Domestic busines 4 Year over 4 Year
3775 W790RC1Q027SBEA_SmoothDer Derivative of Smoothed Net domestic investment: Private: Domestic busines
3776 W790RC1Q027SBEA_Log Log of Net domestic investment: Private: Domestic busines
3778 W790RC1Q027SBEA_mva200 Net domestic investment: Private: Domestic busines 200 Day MA
3779 W790RC1Q027SBEA_mva050 Net domestic investment: Private: Domestic busines 50 Day MA
3780 MZMV_YoY Velocity of MZM Money Stock Year over Year
3781 MZMV_YoY4 Velocity of MZM Money Stock 4 Year over 4 Year
3786 MZMV_Log Log of Velocity of MZM Money Stock
3787 MZMV_mva365 Velocity of MZM Money Stock 365 Day MA
3788 MZMV_mva200 Velocity of MZM Money Stock 200 Day MA
3789 MZMV_mva050 Velocity of MZM Money Stock 50 Day MA
3790 M1_YoY M1 Money Stock Year over Year
3796 M1_Log Log of M1 Money Stock
3797 M1_mva365 M1 Money Stock 365 Day MA
3798 M1_mva200 M1 Money Stock 200 Day MA
3799 M1_mva050 M1 Money Stock 50 Day MA
3800 M2_YoY M2 Money Stock Year over Year
3806 M2_Log Log of M2 Money Stock
3807 M2_mva365 M2 Money Stock 365 Day MA
3808 M2_mva200 M2 Money Stock 200 Day MA
3809 M2_mva050 M2 Money Stock 50 Day MA
3816 OPHNFB_Log Log of Nonfarm Business Sector: Real Output Per Hour of All Persons, SA
3817 OPHNFB_mva365 Nonfarm Business Sector: Real Output Per Hour of All Persons, SA 365 Day MA
3818 OPHNFB_mva200 Nonfarm Business Sector: Real Output Per Hour of All Persons, SA 200 Day MA
3819 OPHNFB_mva050 Nonfarm Business Sector: Real Output Per Hour of All Persons, SA 50 Day MA
3820 IPMAN_YoY Industrial Production: Manufacturing (NAICS) Year over Year
3873 IWD.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3875 IWD.Volume_SmoothDer Derivative of Smoothed
3887 IWD.Adjusted_mva365 365 Day MA
3892 GS5_YoY5 5-Year Treasury Constant Maturity Rate 5 Year over 5 Year
3893 GS5_Smooth Savitsky-Golay Smoothed (p=3, n=365) 5-Year Treasury Constant Maturity Rate
3895 GS5_SmoothDer Derivative of Smoothed 5-Year Treasury Constant Maturity Rate
3896 GS5_Log Log of 5-Year Treasury Constant Maturity Rate
3897 GS5_mva365 5-Year Treasury Constant Maturity Rate 365 Day MA
3898 GS5_mva200 5-Year Treasury Constant Maturity Rate 200 Day MA
3899 GS5_mva050 5-Year Treasury Constant Maturity Rate 50 Day MA
3907 PSAVERT_mva365 Personal Saving Rate 365 Day MA
3913 VIXCLS_Smooth Savitsky-Golay Smoothed (p=3, n=365) CBOE Volatility Index
3915 VIXCLS_SmoothDer Derivative of Smoothed CBOE Volatility Index
3925 VXX.Open_SmoothDer Derivative of Smoothed
3935 VXX.High_SmoothDer Derivative of Smoothed
3945 VXX.Low_SmoothDer Derivative of Smoothed
3955 VXX.Close_SmoothDer Derivative of Smoothed
3966 VXX.Volume_Log Log of
3967 VXX.Volume_mva365 365 Day MA
3975 VXX.Adjusted_SmoothDer Derivative of Smoothed
3982 HOUST1F_YoY5 Privately Owned Housing Starts: 1-Unit Structures 5 Year over 5 Year
3987 HOUST1F_mva365 Privately Owned Housing Starts: 1-Unit Structures 365 Day MA
3989 HOUST1F_mva050 Privately Owned Housing Starts: 1-Unit Structures 50 Day MA
3996 GFDEBTN_Log Log of Federal Debt: Total Public Debt
3997 GFDEBTN_mva365 Federal Debt: Total Public Debt 365 Day MA
3998 GFDEBTN_mva200 Federal Debt: Total Public Debt 200 Day MA
3999 GFDEBTN_mva050 Federal Debt: Total Public Debt 50 Day MA
4002 HOUST_YoY5 Housing Starts: Total: New Privately Owned Housing Units Started, SA 5 Year over 5 Year
4010 HOUSTNSA_YoY Housing Starts: Total: New Privately Owned Housing Units Started, NSA Year over Year
4012 HOUSTNSA_YoY5 Housing Starts: Total: New Privately Owned Housing Units Started, NSA 5 Year over 5 Year
4030 MSPUS_YoY Median Sales Price of Houses Sold for the United States (NSA) Year over Year
4032 MSPUS_YoY5 Median Sales Price of Houses Sold for the United States (NSA) 5 Year over 5 Year
4035 MSPUS_SmoothDer Derivative of Smoothed Median Sales Price of Houses Sold for the United States (NSA)
4036 MSPUS_Log Log of Median Sales Price of Houses Sold for the United States (NSA)
4038 MSPUS_mva200 Median Sales Price of Houses Sold for the United States (NSA) 200 Day MA
4039 MSPUS_mva050 Median Sales Price of Houses Sold for the United States (NSA) 50 Day MA
4057 DGORDER_mva365 Manufacturers’ New Orders: Durable Goods (SA) 365 Day MA
4060 CSUSHPINSA_YoY S&P/Case-Shiller U.S. National Home Price Index (NSA) Year over Year
4062 CSUSHPINSA_YoY5 S&P/Case-Shiller U.S. National Home Price Index (NSA) 5 Year over 5 Year
4066 CSUSHPINSA_Log Log of S&P/Case-Shiller U.S. National Home Price Index (NSA)
4067 CSUSHPINSA_mva365 S&P/Case-Shiller U.S. National Home Price Index (NSA) 365 Day MA
4068 CSUSHPINSA_mva200 S&P/Case-Shiller U.S. National Home Price Index (NSA) 200 Day MA
4069 CSUSHPINSA_mva050 S&P/Case-Shiller U.S. National Home Price Index (NSA) 50 Day MA
4070 GFDEGDQ188S_YoY Federal Debt: Total Public Debt as Percent of Gross Domestic Product Year over Year
4076 GFDEGDQ188S_Log Log of Federal Debt: Total Public Debt as Percent of Gross Domestic Product
4077 GFDEGDQ188S_mva365 Federal Debt: Total Public Debt as Percent of Gross Domestic Product 365 Day MA
4078 GFDEGDQ188S_mva200 Federal Debt: Total Public Debt as Percent of Gross Domestic Product 200 Day MA
4079 GFDEGDQ188S_mva050 Federal Debt: Total Public Debt as Percent of Gross Domestic Product 50 Day MA
4085 FYFSD_SmoothDer Derivative of Smoothed Federal Surplus or Deficit
4086 FYFSD_Log Log of Federal Surplus or Deficit
4090 FYFSGDA188S_YoY Federal Surplus or Deficit [-] as Percent of Gross Domestic Product Year over Year
4094 FYFSGDA188S_Smooth.short Savitsky-Golay Smoothed (p=3, n=15) Federal Surplus or Deficit [-] as Percent of Gross Domestic Product
4096 FYFSGDA188S_Log Log of Federal Surplus or Deficit [-] as Percent of Gross Domestic Product
4097 FYFSGDA188S_mva365 Federal Surplus or Deficit [-] as Percent of Gross Domestic Product 365 Day MA
4098 FYFSGDA188S_mva200 Federal Surplus or Deficit [-] as Percent of Gross Domestic Product 200 Day MA
4099 FYFSGDA188S_mva050 Federal Surplus or Deficit [-] as Percent of Gross Domestic Product 50 Day MA
4107 GDX.Open_mva365 365 Day MA
4117 GDX.High_mva365 365 Day MA
4127 GDX.Low_mva365 365 Day MA
4137 GDX.Close_mva365 365 Day MA
4143 GDX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4145 GDX.Volume_SmoothDer Derivative of Smoothed
4157 GDX.Adjusted_mva365 365 Day MA
4163 XLE.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4165 XLE.Open_SmoothDer Derivative of Smoothed
4173 XLE.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4175 XLE.High_SmoothDer Derivative of Smoothed
4183 XLE.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4185 XLE.Low_SmoothDer Derivative of Smoothed
4193 XLE.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4195 XLE.Close_SmoothDer Derivative of Smoothed
4203 XLE.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4205 XLE.Volume_SmoothDer Derivative of Smoothed
4213 XLE.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4215 XLE.Adjusted_SmoothDer Derivative of Smoothed
4218 XLE.Adjusted_mva200 200 Day MA
4222 GSG.Open_YoY5 5 Year over 5 Year
4223 GSG.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4225 GSG.Open_SmoothDer Derivative of Smoothed
4228 GSG.Open_mva200 200 Day MA
4232 GSG.High_YoY5 5 Year over 5 Year
4233 GSG.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4235 GSG.High_SmoothDer Derivative of Smoothed
4238 GSG.High_mva200 200 Day MA
4242 GSG.Low_YoY5 5 Year over 5 Year
4243 GSG.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4245 GSG.Low_SmoothDer Derivative of Smoothed
4248 GSG.Low_mva200 200 Day MA
4252 GSG.Close_YoY5 5 Year over 5 Year
4253 GSG.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4255 GSG.Close_SmoothDer Derivative of Smoothed
4258 GSG.Close_mva200 200 Day MA
4263 GSG.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4265 GSG.Volume_SmoothDer Derivative of Smoothed
4272 GSG.Adjusted_YoY5 5 Year over 5 Year
4273 GSG.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4275 GSG.Adjusted_SmoothDer Derivative of Smoothed
4278 GSG.Adjusted_mva200 200 Day MA
4290 OUTMS_YoY Manufacturing Sector: Real Output Year over Year
4291 OUTMS_YoY4 Manufacturing Sector: Real Output 4 Year over 4 Year
4292 OUTMS_YoY5 Manufacturing Sector: Real Output 5 Year over 5 Year
4305 MANEMP_SmoothDer Derivative of Smoothed All Employees: Manufacturing
4310 PRS30006163_YoY Manufacturing Sector: Real Output Per Person Year over Year
4311 PRS30006163_YoY4 Manufacturing Sector: Real Output Per Person 4 Year over 4 Year
4312 PRS30006163_YoY5 Manufacturing Sector: Real Output Per Person 5 Year over 5 Year
4325 BAMLC0A3CA_SmoothDer Derivative of Smoothed ICE BofAML US Corporate A Option-Adjusted Spread
4330 AAA_YoY Moody’s Seasoned Aaa Corporate Bond Yield Year over Year
4332 AAA_YoY5 Moody’s Seasoned Aaa Corporate Bond Yield 5 Year over 5 Year
4333 AAA_Smooth Savitsky-Golay Smoothed (p=3, n=365) Moody’s Seasoned Aaa Corporate Bond Yield
4335 AAA_SmoothDer Derivative of Smoothed Moody’s Seasoned Aaa Corporate Bond Yield
4336 AAA_Log Log of Moody’s Seasoned Aaa Corporate Bond Yield
4337 AAA_mva365 Moody’s Seasoned Aaa Corporate Bond Yield 365 Day MA
4338 AAA_mva200 Moody’s Seasoned Aaa Corporate Bond Yield 200 Day MA
4339 AAA_mva050 Moody’s Seasoned Aaa Corporate Bond Yield 50 Day MA
4343 SOFR_Smooth Savitsky-Golay Smoothed (p=3, n=365) Secured Overnight Financing Rate
4347 SOFR_mva365 Secured Overnight Financing Rate 365 Day MA
4348 SOFR_mva200 Secured Overnight Financing Rate 200 Day MA
4353 SOFRVOL_Smooth Savitsky-Golay Smoothed (p=3, n=365) Secured Overnight Financing Volume
4357 SOFRVOL_mva365 Secured Overnight Financing Volume 365 Day MA
4358 SOFRVOL_mva200 Secured Overnight Financing Volume 200 Day MA
4359 SOFRVOL_mva050 Secured Overnight Financing Volume 50 Day MA
4363 SOFR99_Smooth Savitsky-Golay Smoothed (p=3, n=365) Secured Overnight Financing Rate: 99th Percentile
4367 SOFR99_mva365 Secured Overnight Financing Rate: 99th Percentile 365 Day MA
4368 SOFR99_mva200 Secured Overnight Financing Rate: 99th Percentile 200 Day MA
4373 SOFR75_Smooth Savitsky-Golay Smoothed (p=3, n=365) Secured Overnight Financing Rate: 75th Percentile
4377 SOFR75_mva365 Secured Overnight Financing Rate: 75th Percentile 365 Day MA
4378 SOFR75_mva200 Secured Overnight Financing Rate: 75th Percentile 200 Day MA
4383 SOFR25_Smooth Savitsky-Golay Smoothed (p=3, n=365) Secured Overnight Financing Rate: 25th Percentile
4386 SOFR25_Log Log of Secured Overnight Financing Rate: 25th Percentile
4387 SOFR25_mva365 Secured Overnight Financing Rate: 25th Percentile 365 Day MA
4388 SOFR25_mva200 Secured Overnight Financing Rate: 25th Percentile 200 Day MA
4389 SOFR25_mva050 Secured Overnight Financing Rate: 25th Percentile 50 Day MA
4393 SOFR1_Smooth Savitsky-Golay Smoothed (p=3, n=365) Secured Overnight Financing Rate: 1st Percentile
4396 SOFR1_Log Log of Secured Overnight Financing Rate: 1st Percentile
4397 SOFR1_mva365 Secured Overnight Financing Rate: 1st Percentile 365 Day MA
4398 SOFR1_mva200 Secured Overnight Financing Rate: 1st Percentile 200 Day MA
4401 OBFR_YoY4 Overnight Bank Funding Rate 4 Year over 4 Year
4403 OBFR_Smooth Savitsky-Golay Smoothed (p=3, n=365) Overnight Bank Funding Rate
4406 OBFR_Log Log of Overnight Bank Funding Rate
4407 OBFR_mva365 Overnight Bank Funding Rate 365 Day MA
4408 OBFR_mva200 Overnight Bank Funding Rate 200 Day MA
4409 OBFR_mva050 Overnight Bank Funding Rate 50 Day MA
4413 OBFR99_Smooth Savitsky-Golay Smoothed (p=3, n=365) Overnight Bank Funding Rate: 99th Percentile
4417 OBFR99_mva365 Overnight Bank Funding Rate: 99th Percentile 365 Day MA
4418 OBFR99_mva200 Overnight Bank Funding Rate: 99th Percentile 200 Day MA
4421 OBFR75_YoY4 Overnight Bank Funding Rate: 75th Percentile 4 Year over 4 Year
4423 OBFR75_Smooth Savitsky-Golay Smoothed (p=3, n=365) Overnight Bank Funding Rate: 75th Percentile
4426 OBFR75_Log Log of Overnight Bank Funding Rate: 75th Percentile
4427 OBFR75_mva365 Overnight Bank Funding Rate: 75th Percentile 365 Day MA
4428 OBFR75_mva200 Overnight Bank Funding Rate: 75th Percentile 200 Day MA
4429 OBFR75_mva050 Overnight Bank Funding Rate: 75th Percentile 50 Day MA
4433 OBFR25_Smooth Savitsky-Golay Smoothed (p=3, n=365) Overnight Bank Funding Rate: 25th Percentile
4436 OBFR25_Log Log of Overnight Bank Funding Rate: 25th Percentile
4437 OBFR25_mva365 Overnight Bank Funding Rate: 25th Percentile 365 Day MA
4438 OBFR25_mva200 Overnight Bank Funding Rate: 25th Percentile 200 Day MA
4439 OBFR25_mva050 Overnight Bank Funding Rate: 25th Percentile 50 Day MA
4447 OBFR1_mva365 Overnight Bank Funding Rate: 1st Percentile 365 Day MA
4448 OBFR1_mva200 Overnight Bank Funding Rate: 1st Percentile 200 Day MA
4453 RPONTSYD_Smooth Savitsky-Golay Smoothed (p=3, n=365) Overnight Repurchase Agreements: Treasury Securities Purchased by the Federal Reserve in the Temporary Open Market Operations
4455 RPONTSYD_SmoothDer Derivative of Smoothed Overnight Repurchase Agreements: Treasury Securities Purchased by the Federal Reserve in the Temporary Open Market Operations
4456 RPONTSYD_Log Log of Overnight Repurchase Agreements: Treasury Securities Purchased by the Federal Reserve in the Temporary Open Market Operations
4460 IOER_YoY Interest Rate on Excess Reserves Year over Year
4461 IOER_YoY4 Interest Rate on Excess Reserves 4 Year over 4 Year
4466 IOER_Log Log of Interest Rate on Excess Reserves
4467 IOER_mva365 Interest Rate on Excess Reserves 365 Day MA
4468 IOER_mva200 Interest Rate on Excess Reserves 200 Day MA
4469 IOER_mva050 Interest Rate on Excess Reserves 50 Day MA
4472 WRESBAL_YoY5 Reserve Balances with Federal Reserve Banks 5 Year over 5 Year
4473 WRESBAL_Smooth Savitsky-Golay Smoothed (p=3, n=365) Reserve Balances with Federal Reserve Banks
4476 WRESBAL_Log Log of Reserve Balances with Federal Reserve Banks
4477 WRESBAL_mva365 Reserve Balances with Federal Reserve Banks 365 Day MA
4479 WRESBAL_mva050 Reserve Balances with Federal Reserve Banks 50 Day MA
4480 EXCSRESNW_YoY Excess Reserves of Depository Institutions Year over Year
4482 EXCSRESNW_YoY5 Excess Reserves of Depository Institutions 5 Year over 5 Year
4486 EXCSRESNW_Log Log of Excess Reserves of Depository Institutions
4487 EXCSRESNW_mva365 Excess Reserves of Depository Institutions 365 Day MA
4488 EXCSRESNW_mva200 Excess Reserves of Depository Institutions 200 Day MA
4489 EXCSRESNW_mva050 Excess Reserves of Depository Institutions 50 Day MA
4490 ECBASSETS_YoY Central Bank Assets for Euro Area (11-19 Countries) Year over Year
4496 ECBASSETS_Log Log of Central Bank Assets for Euro Area (11-19 Countries)
4497 ECBASSETS_mva365 Central Bank Assets for Euro Area (11-19 Countries) 365 Day MA
4498 ECBASSETS_mva200 Central Bank Assets for Euro Area (11-19 Countries) 200 Day MA
4499 ECBASSETS_mva050 Central Bank Assets for Euro Area (11-19 Countries) 50 Day MA
4501 EUNNGDP_YoY4 Gross Domestic Product (Euro/ECU series) for Euro Area (19 Countries) 4 Year over 4 Year
4506 EUNNGDP_Log Log of Gross Domestic Product (Euro/ECU series) for Euro Area (19 Countries)
4507 EUNNGDP_mva365 Gross Domestic Product (Euro/ECU series) for Euro Area (19 Countries) 365 Day MA
4508 EUNNGDP_mva200 Gross Domestic Product (Euro/ECU series) for Euro Area (19 Countries) 200 Day MA
4509 EUNNGDP_mva050 Gross Domestic Product (Euro/ECU series) for Euro Area (19 Countries) 50 Day MA
4510 CEU0600000007_YoY Average Weekly Hours of Production and Nonsupervisory Employees: Goods-Producing Year over Year
4516 CEU0600000007_Log Log of Average Weekly Hours of Production and Nonsupervisory Employees: Goods-Producing
4517 CEU0600000007_mva365 Average Weekly Hours of Production and Nonsupervisory Employees: Goods-Producing 365 Day MA
4518 CEU0600000007_mva200 Average Weekly Hours of Production and Nonsupervisory Employees: Goods-Producing 200 Day MA
4519 CEU0600000007_mva050 Average Weekly Hours of Production and Nonsupervisory Employees: Goods-Producing 50 Day MA
4520 CURRENCY_YoY Currency Component of M1 (Seasonally Adjusted) Year over Year
4526 CURRENCY_Log Log of Currency Component of M1 (Seasonally Adjusted)
4527 CURRENCY_mva365 Currency Component of M1 (Seasonally Adjusted) 365 Day MA
4528 CURRENCY_mva200 Currency Component of M1 (Seasonally Adjusted) 200 Day MA
4529 CURRENCY_mva050 Currency Component of M1 (Seasonally Adjusted) 50 Day MA
4537 WCURRNS_mva365 Currency Component of M1 365 Day MA
4542 BOGMBASE_YoY5 Monetary Base; Total 5 Year over 5 Year
4547 BOGMBASE_mva365 Monetary Base; Total 365 Day MA
4550 PRS88003193_YoY Nonfinancial Corporations Sector: Unit Profits Year over Year
4551 PRS88003193_YoY4 Nonfinancial Corporations Sector: Unit Profits 4 Year over 4 Year
4552 PRS88003193_YoY5 Nonfinancial Corporations Sector: Unit Profits 5 Year over 5 Year
4556 PRS88003193_Log Log of Nonfinancial Corporations Sector: Unit Profits
4558 PRS88003193_mva200 Nonfinancial Corporations Sector: Unit Profits 200 Day MA
4559 PRS88003193_mva050 Nonfinancial Corporations Sector: Unit Profits 50 Day MA
4560 PPIACO_YoY Producer Price Index for All Commodities Year over Year
4565 PPIACO_SmoothDer Derivative of Smoothed Producer Price Index for All Commodities
4570 PCUOMFGOMFG_YoY Producer Price Index by Industry: Total Manufacturing Industries Year over Year
4572 PCUOMFGOMFG_YoY5 Producer Price Index by Industry: Total Manufacturing Industries 5 Year over 5 Year
4573 PCUOMFGOMFG_Smooth Savitsky-Golay Smoothed (p=3, n=365) Producer Price Index by Industry: Total Manufacturing Industries
4575 PCUOMFGOMFG_SmoothDer Derivative of Smoothed Producer Price Index by Industry: Total Manufacturing Industries
4578 PCUOMFGOMFG_mva200 Producer Price Index by Industry: Total Manufacturing Industries 200 Day MA
4592 POPTHM_Log Log of Population (U.S.)
4593 POPTHM_Log Log of Population (U.S.)
4594 POPTHM_mva365 Population (U.S.) 365 Day MA
4595 POPTHM_mva365 Population (U.S.) 365 Day MA
4596 POPTHM_mva200 Population (U.S.) 200 Day MA
4597 POPTHM_mva200 Population (U.S.) 200 Day MA
4598 POPTHM_mva050 Population (U.S.) 50 Day MA
4599 POPTHM_mva050 Population (U.S.) 50 Day MA
4612 POPTHM.1_Log Log of
4613 POPTHM.1_Log Log of
4614 POPTHM.1_mva365 365 Day MA
4615 POPTHM.1_mva365 365 Day MA
4616 POPTHM.1_mva200 200 Day MA
4617 POPTHM.1_mva200 200 Day MA
4618 POPTHM.1_mva050 50 Day MA
4619 POPTHM.1_mva050 50 Day MA
4623 CLF16OV_Smooth Savitsky-Golay Smoothed (p=3, n=365) Civilian Labor Force Level, SA
4627 CLF16OV_mva365 Civilian Labor Force Level, SA 365 Day MA
4628 CLF16OV_mva200 Civilian Labor Force Level, SA 200 Day MA
4630 LNU01000000_YoY Civilian Labor Force Level, NSA Year over Year
4637 LNU01000000_mva365 Civilian Labor Force Level, NSA 365 Day MA
4638 LNU01000000_mva200 Civilian Labor Force Level, NSA 200 Day MA
4640 LNU03000000_YoY Unemployment Level (NSA) Year over Year
4647 LNU03000000_mva365 Unemployment Level (NSA) 365 Day MA
4648 LNU03000000_mva200 Unemployment Level (NSA) 200 Day MA
4650 UNEMPLOY_YoY Unemployment Level, seasonally adjusted Year over Year
4651 UNEMPLOY_YoY4 Unemployment Level, seasonally adjusted 4 Year over 4 Year
4653 UNEMPLOY_Smooth Savitsky-Golay Smoothed (p=3, n=365) Unemployment Level, seasonally adjusted
4655 UNEMPLOY_SmoothDer Derivative of Smoothed Unemployment Level, seasonally adjusted
4656 UNEMPLOY_Log Log of Unemployment Level, seasonally adjusted
4657 UNEMPLOY_mva365 Unemployment Level, seasonally adjusted 365 Day MA
4658 UNEMPLOY_mva200 Unemployment Level, seasonally adjusted 200 Day MA
4659 UNEMPLOY_mva050 Unemployment Level, seasonally adjusted 50 Day MA
4660 RSAFS_YoY Advance Retail Sales: Retail and Food Services Year over Year
4663 RSAFS_Smooth Savitsky-Golay Smoothed (p=3, n=365) Advance Retail Sales: Retail and Food Services
4665 RSAFS_SmoothDer Derivative of Smoothed Advance Retail Sales: Retail and Food Services
4667 RSAFS_mva365 Advance Retail Sales: Retail and Food Services 365 Day MA
4668 RSAFS_mva200 Advance Retail Sales: Retail and Food Services 200 Day MA
4671 FRGSHPUSM649NCIS_YoY4 Cass Freight Index: Shipments 4 Year over 4 Year
4672 FRGSHPUSM649NCIS_YoY5 Cass Freight Index: Shipments 5 Year over 5 Year
4683 BOPGTB_Smooth Savitsky-Golay Smoothed (p=3, n=365) Trade Balance: Goods, Balance of Payments Basis (SA)
4686 BOPGTB_Log Log of Trade Balance: Goods, Balance of Payments Basis (SA)
4687 BOPGTB_mva365 Trade Balance: Goods, Balance of Payments Basis (SA) 365 Day MA
4688 BOPGTB_mva200 Trade Balance: Goods, Balance of Payments Basis (SA) 200 Day MA
4695 TERMCBPER24NS_SmoothDer Derivative of Smoothed Finance Rate on Personal Loans at Commercial Banks, 24 Month Loan
4696 TERMCBPER24NS_Log Log of Finance Rate on Personal Loans at Commercial Banks, 24 Month Loan
4697 TERMCBPER24NS_mva365 Finance Rate on Personal Loans at Commercial Banks, 24 Month Loan 365 Day MA
4698 TERMCBPER24NS_mva200 Finance Rate on Personal Loans at Commercial Banks, 24 Month Loan 200 Day MA
4699 TERMCBPER24NS_mva050 Finance Rate on Personal Loans at Commercial Banks, 24 Month Loan 50 Day MA
4700 A065RC1A027NBEA_YoY Personal income (NSA) Year over Year
4706 A065RC1A027NBEA_Log Log of Personal income (NSA)
4707 A065RC1A027NBEA_mva365 Personal income (NSA) 365 Day MA
4708 A065RC1A027NBEA_mva200 Personal income (NSA) 200 Day MA
4709 A065RC1A027NBEA_mva050 Personal income (NSA) 50 Day MA
4713 PI_Smooth Savitsky-Golay Smoothed (p=3, n=365) Personal income (SA)
4716 PI_Log Log of Personal income (SA)
4717 PI_mva365 Personal income (SA) 365 Day MA
4718 PI_mva200 Personal income (SA) 200 Day MA
4719 PI_mva050 Personal income (SA) 50 Day MA
4723 PCE_Smooth Savitsky-Golay Smoothed (p=3, n=365) Personal Consumption Expenditures (SA)
4726 PCE_Log Log of Personal Consumption Expenditures (SA)
4727 PCE_mva365 Personal Consumption Expenditures (SA) 365 Day MA
4728 PCE_mva200 Personal Consumption Expenditures (SA) 200 Day MA
4729 PCE_mva050 Personal Consumption Expenditures (SA) 50 Day MA
4731 A053RC1Q027SBEA_YoY4 National income: Corporate profits before tax (without IVA and CCAdj) 4 Year over 4 Year
4733 A053RC1Q027SBEA_Smooth Savitsky-Golay Smoothed (p=3, n=365) National income: Corporate profits before tax (without IVA and CCAdj)
4736 A053RC1Q027SBEA_Log Log of National income: Corporate profits before tax (without IVA and CCAdj)
4738 A053RC1Q027SBEA_mva200 National income: Corporate profits before tax (without IVA and CCAdj) 200 Day MA
4739 A053RC1Q027SBEA_mva050 National income: Corporate profits before tax (without IVA and CCAdj) 50 Day MA
4740 CPROFIT_YoY Corporate Profits with Inventory Valuation Adjustment (IVA) and Capital Consumption Adjustment (CCAdj) Year over Year
4741 CPROFIT_YoY4 Corporate Profits with Inventory Valuation Adjustment (IVA) and Capital Consumption Adjustment (CCAdj) 4 Year over 4 Year
4746 CPROFIT_Log Log of Corporate Profits with Inventory Valuation Adjustment (IVA) and Capital Consumption Adjustment (CCAdj)
4749 CPROFIT_mva050 Corporate Profits with Inventory Valuation Adjustment (IVA) and Capital Consumption Adjustment (CCAdj) 50 Day MA
4752 SPY.Open_YoY5 5 Year over 5 Year
4757 SPY.Open_mva365 365 Day MA
4758 SPY.Open_mva200 200 Day MA
4762 SPY.High_YoY5 5 Year over 5 Year
4767 SPY.High_mva365 365 Day MA
4768 SPY.High_mva200 200 Day MA
4772 SPY.Low_YoY5 5 Year over 5 Year
4777 SPY.Low_mva365 365 Day MA
4778 SPY.Low_mva200 200 Day MA
4782 SPY.Close_YoY5 5 Year over 5 Year
4787 SPY.Close_mva365 365 Day MA
4788 SPY.Close_mva200 200 Day MA
4793 SPY.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4795 SPY.Volume_SmoothDer Derivative of Smoothed
4802 SPY.Adjusted_YoY5 5 Year over 5 Year
4807 SPY.Adjusted_mva365 365 Day MA
4808 SPY.Adjusted_mva200 200 Day MA
4812 MDY.Open_YoY5 5 Year over 5 Year
4853 MDY.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4855 MDY.Volume_SmoothDer Derivative of Smoothed
4857 MDY.Volume_mva365 365 Day MA
4867 MDY.Adjusted_mva365 365 Day MA
4913 EES.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4915 EES.Volume_SmoothDer Derivative of Smoothed
4916 EES.Volume_Log Log of
4973 IJR.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4975 IJR.Volume_SmoothDer Derivative of Smoothed
5030 VGSTX.Volume_YoY Year over Year
5031 VGSTX.Volume_YoY4 4 Year over 4 Year
5032 VGSTX.Volume_YoY5 5 Year over 5 Year
5033 VGSTX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5034 VGSTX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
5035 VGSTX.Volume_SmoothDer Derivative of Smoothed
5036 VGSTX.Volume_Log Log of
5037 VGSTX.Volume_mva365 365 Day MA
5038 VGSTX.Volume_mva200 200 Day MA
5039 VGSTX.Volume_mva050 50 Day MA
5047 VGSTX.Adjusted_mva365 365 Day MA
5052 VFINX.Open_YoY5 5 Year over 5 Year
5057 VFINX.Open_mva365 365 Day MA
5058 VFINX.Open_mva200 200 Day MA
5062 VFINX.High_YoY5 5 Year over 5 Year
5067 VFINX.High_mva365 365 Day MA
5068 VFINX.High_mva200 200 Day MA
5072 VFINX.Low_YoY5 5 Year over 5 Year
5077 VFINX.Low_mva365 365 Day MA
5078 VFINX.Low_mva200 200 Day MA
5082 VFINX.Close_YoY5 5 Year over 5 Year
5087 VFINX.Close_mva365 365 Day MA
5088 VFINX.Close_mva200 200 Day MA
5090 VFINX.Volume_YoY Year over Year
5091 VFINX.Volume_YoY4 4 Year over 4 Year
5092 VFINX.Volume_YoY5 5 Year over 5 Year
5093 VFINX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5094 VFINX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
5095 VFINX.Volume_SmoothDer Derivative of Smoothed
5096 VFINX.Volume_Log Log of
5097 VFINX.Volume_mva365 365 Day MA
5098 VFINX.Volume_mva200 200 Day MA
5099 VFINX.Volume_mva050 50 Day MA
5102 VFINX.Adjusted_YoY5 5 Year over 5 Year
5107 VFINX.Adjusted_mva365 365 Day MA
5108 VFINX.Adjusted_mva200 200 Day MA
5112 VOE.Open_YoY5 5 Year over 5 Year
5153 VOE.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5155 VOE.Volume_SmoothDer Derivative of Smoothed
5177 VOT.Open_mva365 365 Day MA
5187 VOT.High_mva365 365 Day MA
5197 VOT.Low_mva365 365 Day MA
5207 VOT.Close_mva365 365 Day MA
5213 VOT.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5215 VOT.Volume_SmoothDer Derivative of Smoothed
5219 VOT.Volume_mva050 50 Day MA
5227 VOT.Adjusted_mva365 365 Day MA
5230 TMFGX.Open_YoY Year over Year
5232 TMFGX.Open_YoY5 5 Year over 5 Year
5236 TMFGX.Open_Log Log of
5237 TMFGX.Open_mva365 365 Day MA
5238 TMFGX.Open_mva200 200 Day MA
5239 TMFGX.Open_mva050 50 Day MA
5240 TMFGX.High_YoY Year over Year
5242 TMFGX.High_YoY5 5 Year over 5 Year
5246 TMFGX.High_Log Log of
5247 TMFGX.High_mva365 365 Day MA
5248 TMFGX.High_mva200 200 Day MA
5249 TMFGX.High_mva050 50 Day MA
5250 TMFGX.Low_YoY Year over Year
5252 TMFGX.Low_YoY5 5 Year over 5 Year
5256 TMFGX.Low_Log Log of
5257 TMFGX.Low_mva365 365 Day MA
5258 TMFGX.Low_mva200 200 Day MA
5259 TMFGX.Low_mva050 50 Day MA
5260 TMFGX.Close_YoY Year over Year
5262 TMFGX.Close_YoY5 5 Year over 5 Year
5266 TMFGX.Close_Log Log of
5267 TMFGX.Close_mva365 365 Day MA
5268 TMFGX.Close_mva200 200 Day MA
5269 TMFGX.Close_mva050 50 Day MA
5270 TMFGX.Volume_YoY Year over Year
5271 TMFGX.Volume_YoY4 4 Year over 4 Year
5272 TMFGX.Volume_YoY5 5 Year over 5 Year
5273 TMFGX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5274 TMFGX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
5275 TMFGX.Volume_SmoothDer Derivative of Smoothed
5276 TMFGX.Volume_Log Log of
5277 TMFGX.Volume_mva365 365 Day MA
5278 TMFGX.Volume_mva200 200 Day MA
5279 TMFGX.Volume_mva050 50 Day MA
5280 TMFGX.Adjusted_YoY Year over Year
5282 TMFGX.Adjusted_YoY5 5 Year over 5 Year
5286 TMFGX.Adjusted_Log Log of
5287 TMFGX.Adjusted_mva365 365 Day MA
5288 TMFGX.Adjusted_mva200 200 Day MA
5289 TMFGX.Adjusted_mva050 50 Day MA
5333 IWM.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5335 IWM.Volume_SmoothDer Derivative of Smoothed
5337 IWM.Volume_mva365 365 Day MA
5357 ONEQ.Open_mva365 365 Day MA
5358 ONEQ.Open_mva200 200 Day MA
5367 ONEQ.High_mva365 365 Day MA
5368 ONEQ.High_mva200 200 Day MA
5377 ONEQ.Low_mva365 365 Day MA
5378 ONEQ.Low_mva200 200 Day MA
5387 ONEQ.Close_mva365 365 Day MA
5388 ONEQ.Close_mva200 200 Day MA
5395 ONEQ.Volume_SmoothDer Derivative of Smoothed
5407 ONEQ.Adjusted_mva365 365 Day MA
5408 ONEQ.Adjusted_mva200 200 Day MA
5417 FSMAX.Open_mva365 365 Day MA
5418 FSMAX.Open_mva200 200 Day MA
5427 FSMAX.High_mva365 365 Day MA
5428 FSMAX.High_mva200 200 Day MA
5437 FSMAX.Low_mva365 365 Day MA
5438 FSMAX.Low_mva200 200 Day MA
5447 FSMAX.Close_mva365 365 Day MA
5448 FSMAX.Close_mva200 200 Day MA
5450 FSMAX.Volume_YoY Year over Year
5451 FSMAX.Volume_YoY4 4 Year over 4 Year
5452 FSMAX.Volume_YoY5 5 Year over 5 Year
5453 FSMAX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5454 FSMAX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
5455 FSMAX.Volume_SmoothDer Derivative of Smoothed
5456 FSMAX.Volume_Log Log of
5457 FSMAX.Volume_mva365 365 Day MA
5458 FSMAX.Volume_mva200 200 Day MA
5459 FSMAX.Volume_mva050 50 Day MA
5467 FSMAX.Adjusted_mva365 365 Day MA
5468 FSMAX.Adjusted_mva200 200 Day MA
5510 FXNAX.Volume_YoY Year over Year
5511 FXNAX.Volume_YoY4 4 Year over 4 Year
5512 FXNAX.Volume_YoY5 5 Year over 5 Year
5513 FXNAX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5514 FXNAX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
5515 FXNAX.Volume_SmoothDer Derivative of Smoothed
5516 FXNAX.Volume_Log Log of
5517 FXNAX.Volume_mva365 365 Day MA
5518 FXNAX.Volume_mva200 200 Day MA
5519 FXNAX.Volume_mva050 50 Day MA
5537 HAINX.Open_mva365 365 Day MA
5547 HAINX.High_mva365 365 Day MA
5557 HAINX.Low_mva365 365 Day MA
5567 HAINX.Close_mva365 365 Day MA
5570 HAINX.Volume_YoY Year over Year
5571 HAINX.Volume_YoY4 4 Year over 4 Year
5572 HAINX.Volume_YoY5 5 Year over 5 Year
5573 HAINX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5574 HAINX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
5575 HAINX.Volume_SmoothDer Derivative of Smoothed
5576 HAINX.Volume_Log Log of
5577 HAINX.Volume_mva365 365 Day MA
5578 HAINX.Volume_mva200 200 Day MA
5579 HAINX.Volume_mva050 50 Day MA
5587 HAINX.Adjusted_mva365 365 Day MA
5594 HNACX.Open_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
5597 HNACX.Open_mva365 365 Day MA
5598 HNACX.Open_mva200 200 Day MA
5604 HNACX.High_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
5607 HNACX.High_mva365 365 Day MA
5608 HNACX.High_mva200 200 Day MA
5614 HNACX.Low_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
5617 HNACX.Low_mva365 365 Day MA
5618 HNACX.Low_mva200 200 Day MA
5624 HNACX.Close_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
5627 HNACX.Close_mva365 365 Day MA
5628 HNACX.Close_mva200 200 Day MA
5630 HNACX.Volume_YoY Year over Year
5631 HNACX.Volume_YoY4 4 Year over 4 Year
5632 HNACX.Volume_YoY5 5 Year over 5 Year
5633 HNACX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5634 HNACX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
5635 HNACX.Volume_SmoothDer Derivative of Smoothed
5636 HNACX.Volume_Log Log of
5637 HNACX.Volume_mva365 365 Day MA
5638 HNACX.Volume_mva200 200 Day MA
5639 HNACX.Volume_mva050 50 Day MA
5644 HNACX.Adjusted_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
5647 HNACX.Adjusted_mva365 365 Day MA
5648 HNACX.Adjusted_mva200 200 Day MA
5652 VEU.Open_YoY5 5 Year over 5 Year
5657 VEU.Open_mva365 365 Day MA
5667 VEU.High_mva365 365 Day MA
5677 VEU.Low_mva365 365 Day MA
5687 VEU.Close_mva365 365 Day MA
5693 VEU.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5695 VEU.Volume_SmoothDer Derivative of Smoothed
5707 VEU.Adjusted_mva365 365 Day MA
5715 VEIRX.Open_SmoothDer Derivative of Smoothed
5725 VEIRX.High_SmoothDer Derivative of Smoothed
5735 VEIRX.Low_SmoothDer Derivative of Smoothed
5745 VEIRX.Close_SmoothDer Derivative of Smoothed
5750 VEIRX.Volume_YoY Year over Year
5751 VEIRX.Volume_YoY4 4 Year over 4 Year
5752 VEIRX.Volume_YoY5 5 Year over 5 Year
5753 VEIRX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5754 VEIRX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
5755 VEIRX.Volume_SmoothDer Derivative of Smoothed
5756 VEIRX.Volume_Log Log of
5757 VEIRX.Volume_mva365 365 Day MA
5758 VEIRX.Volume_mva200 200 Day MA
5759 VEIRX.Volume_mva050 50 Day MA
5773 BIL.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5777 BIL.Open_mva365 365 Day MA
5783 BIL.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5787 BIL.High_mva365 365 Day MA
5793 BIL.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5797 BIL.Low_mva365 365 Day MA
5803 BIL.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5807 BIL.Close_mva365 365 Day MA
5813 BIL.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5815 BIL.Volume_SmoothDer Derivative of Smoothed
5817 BIL.Volume_mva365 365 Day MA
5818 BIL.Volume_mva200 200 Day MA
5820 BIL.Adjusted_YoY Year over Year
5821 BIL.Adjusted_YoY4 4 Year over 4 Year
5823 BIL.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5824 BIL.Adjusted_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
5826 BIL.Adjusted_Log Log of
5827 BIL.Adjusted_mva365 365 Day MA
5828 BIL.Adjusted_mva200 200 Day MA
5829 BIL.Adjusted_mva050 50 Day MA
5832 IVOO.Open_YoY5 5 Year over 5 Year
5873 IVOO.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5875 IVOO.Volume_SmoothDer Derivative of Smoothed
5876 IVOO.Volume_Log Log of
5879 IVOO.Volume_mva050 50 Day MA
5887 IVOO.Adjusted_mva365 365 Day MA
5892 VO.Open_YoY5 5 Year over 5 Year
5897 VO.Open_mva365 365 Day MA
5917 VO.Low_mva365 365 Day MA
5927 VO.Close_mva365 365 Day MA
5933 VO.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5935 VO.Volume_SmoothDer Derivative of Smoothed
5936 VO.Volume_Log Log of
5947 VO.Adjusted_mva365 365 Day MA
5993 CZA.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5995 CZA.Volume_SmoothDer Derivative of Smoothed
5996 CZA.Volume_Log Log of
6055 VYM.Volume_SmoothDer Derivative of Smoothed
6072 ACWI.Open_YoY5 5 Year over 5 Year
6077 ACWI.Open_mva365 365 Day MA
6078 ACWI.Open_mva200 200 Day MA
6087 ACWI.High_mva365 365 Day MA
6088 ACWI.High_mva200 200 Day MA
6097 ACWI.Low_mva365 365 Day MA
6098 ACWI.Low_mva200 200 Day MA
6107 ACWI.Close_mva365 365 Day MA
6108 ACWI.Close_mva200 200 Day MA
6113 ACWI.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
6115 ACWI.Volume_SmoothDer Derivative of Smoothed
6119 ACWI.Volume_mva050 50 Day MA
6127 ACWI.Adjusted_mva365 365 Day MA
6128 ACWI.Adjusted_mva200 200 Day MA
6133 SLY.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
6135 SLY.Open_SmoothDer Derivative of Smoothed
6138 SLY.Open_mva200 200 Day MA
6143 SLY.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
6145 SLY.High_SmoothDer Derivative of Smoothed
6153 SLY.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
6155 SLY.Low_SmoothDer Derivative of Smoothed
6158 SLY.Low_mva200 200 Day MA
6163 SLY.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
6165 SLY.Close_SmoothDer Derivative of Smoothed
6175 SLY.Volume_SmoothDer Derivative of Smoothed
6176 SLY.Volume_Log Log of
6183 SLY.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
6185 SLY.Adjusted_SmoothDer Derivative of Smoothed
6196 QQQ.Open_Log Log of
6197 QQQ.Open_mva365 365 Day MA
6198 QQQ.Open_mva200 200 Day MA
6207 QQQ.High_mva365 365 Day MA
6208 QQQ.High_mva200 200 Day MA
6216 QQQ.Low_Log Log of
6217 QQQ.Low_mva365 365 Day MA
6218 QQQ.Low_mva200 200 Day MA
6227 QQQ.Close_mva365 365 Day MA
6228 QQQ.Close_mva200 200 Day MA
6233 QQQ.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
6235 QQQ.Volume_SmoothDer Derivative of Smoothed
6247 QQQ.Adjusted_mva365 365 Day MA
6248 QQQ.Adjusted_mva200 200 Day MA
6293 HYMB.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
6295 HYMB.Volume_SmoothDer Derivative of Smoothed
6296 HYMB.Volume_Log Log of
6299 HYMB.Volume_mva050 50 Day MA
6307 HYMB.Adjusted_mva365 365 Day MA
6316 GOLD.Open_Log Log of
6353 GOLD.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
6355 GOLD.Volume_SmoothDer Derivative of Smoothed
6356 GOLD.Volume_Log Log of
6367 GOLD.Adjusted_mva365 365 Day MA
6372 BKR.Open_YoY5 5 Year over 5 Year
6375 BKR.Open_SmoothDer Derivative of Smoothed
6376 BKR.Open_Log Log of
6377 BKR.Open_mva365 365 Day MA
6378 BKR.Open_mva200 200 Day MA
6385 BKR.High_SmoothDer Derivative of Smoothed
6387 BKR.High_mva365 365 Day MA
6388 BKR.High_mva200 200 Day MA
6395 BKR.Low_SmoothDer Derivative of Smoothed
6397 BKR.Low_mva365 365 Day MA
6398 BKR.Low_mva200 200 Day MA
6405 BKR.Close_SmoothDer Derivative of Smoothed
6407 BKR.Close_mva365 365 Day MA
6408 BKR.Close_mva200 200 Day MA
6415 BKR.Volume_SmoothDer Derivative of Smoothed
6416 BKR.Volume_Log Log of
6425 BKR.Adjusted_SmoothDer Derivative of Smoothed
6427 BKR.Adjusted_mva365 365 Day MA
6428 BKR.Adjusted_mva200 200 Day MA
6433 SLB.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
6435 SLB.Open_SmoothDer Derivative of Smoothed
6438 SLB.Open_mva200 200 Day MA
6443 SLB.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
6445 SLB.High_SmoothDer Derivative of Smoothed
6448 SLB.High_mva200 200 Day MA
6453 SLB.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
6455 SLB.Low_SmoothDer Derivative of Smoothed
6457 SLB.Low_mva365 365 Day MA
6458 SLB.Low_mva200 200 Day MA
6463 SLB.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
6465 SLB.Close_SmoothDer Derivative of Smoothed
6468 SLB.Close_mva200 200 Day MA
6475 SLB.Volume_SmoothDer Derivative of Smoothed
6483 SLB.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
6485 SLB.Adjusted_SmoothDer Derivative of Smoothed
6487 SLB.Adjusted_mva365 365 Day MA
6488 SLB.Adjusted_mva200 200 Day MA
6493 HAL.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
6495 HAL.Open_SmoothDer Derivative of Smoothed
6496 HAL.Open_Log Log of
6497 HAL.Open_mva365 365 Day MA
6498 HAL.Open_mva200 200 Day MA
6502 HAL.High_YoY5 5 Year over 5 Year
6503 HAL.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
6505 HAL.High_SmoothDer Derivative of Smoothed
6507 HAL.High_mva365 365 Day MA
6508 HAL.High_mva200 200 Day MA
6513 HAL.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
6515 HAL.Low_SmoothDer Derivative of Smoothed
6517 HAL.Low_mva365 365 Day MA
6518 HAL.Low_mva200 200 Day MA
6522 HAL.Close_YoY5 5 Year over 5 Year
6523 HAL.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
6525 HAL.Close_SmoothDer Derivative of Smoothed
6527 HAL.Close_mva365 365 Day MA
6528 HAL.Close_mva200 200 Day MA
6536 HAL.Volume_Log Log of
6542 HAL.Adjusted_YoY5 5 Year over 5 Year
6543 HAL.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
6545 HAL.Adjusted_SmoothDer Derivative of Smoothed
6547 HAL.Adjusted_mva365 365 Day MA
6548 HAL.Adjusted_mva200 200 Day MA
6553 IP.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
6556 IP.Open_Log Log of
6563 IP.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
6573 IP.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
6583 IP.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
6595 IP.Volume_SmoothDer Derivative of Smoothed
6603 IP.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
6613 PKG.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
6617 PKG.Open_mva365 365 Day MA
6618 PKG.Open_mva200 200 Day MA
6619 PKG.Open_mva050 50 Day MA
6623 PKG.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
6627 PKG.High_mva365 365 Day MA
6628 PKG.High_mva200 200 Day MA
6629 PKG.High_mva050 50 Day MA
6633 PKG.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
6637 PKG.Low_mva365 365 Day MA
6638 PKG.Low_mva200 200 Day MA
6643 PKG.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
6647 PKG.Close_mva365 365 Day MA
6648 PKG.Close_mva200 200 Day MA
6655 PKG.Volume_SmoothDer Derivative of Smoothed
6663 PKG.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
6667 PKG.Adjusted_mva365 365 Day MA
6668 PKG.Adjusted_mva200 200 Day MA
6713 UPS.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
6715 UPS.Volume_SmoothDer Derivative of Smoothed
6717 UPS.Volume_mva365 365 Day MA
6737 FDX.Open_mva365 365 Day MA
6738 FDX.Open_mva200 200 Day MA
6747 FDX.High_mva365 365 Day MA
6748 FDX.High_mva200 200 Day MA
6757 FDX.Low_mva365 365 Day MA
6758 FDX.Low_mva200 200 Day MA
6767 FDX.Close_mva365 365 Day MA
6768 FDX.Close_mva200 200 Day MA
6775 FDX.Volume_SmoothDer Derivative of Smoothed
6787 FDX.Adjusted_mva365 365 Day MA
6788 FDX.Adjusted_mva200 200 Day MA
6792 T.Open_YoY5 5 Year over 5 Year
6794 T.Open_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
6795 T.Open_SmoothDer Derivative of Smoothed
6796 T.Open_Log Log of
6802 T.High_YoY5 5 Year over 5 Year
6804 T.High_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
6805 T.High_SmoothDer Derivative of Smoothed
6806 T.High_Log Log of
6812 T.Low_YoY5 5 Year over 5 Year
6814 T.Low_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
6815 T.Low_SmoothDer Derivative of Smoothed
6816 T.Low_Log Log of
6822 T.Close_YoY5 5 Year over 5 Year
6824 T.Close_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
6825 T.Close_SmoothDer Derivative of Smoothed
6826 T.Close_Log Log of
6842 T.Adjusted_YoY5 5 Year over 5 Year
6843 T.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
6844 T.Adjusted_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
6845 T.Adjusted_SmoothDer Derivative of Smoothed
6846 T.Adjusted_Log Log of
6895 VZ.Volume_SmoothDer Derivative of Smoothed
6903 VZ.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
6904 VZ.Adjusted_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
6906 VZ.Adjusted_Log Log of
6910 ISMMANPMI_YoY Institute of Supply Managment PMI Composite Index Year over Year
6911 ISMMANPMI_YoY4 Institute of Supply Managment PMI Composite Index 4 Year over 4 Year
6912 ISMMANPMI_YoY5 Institute of Supply Managment PMI Composite Index 5 Year over 5 Year
6916 ISMMANPMI_Log Log of Institute of Supply Managment PMI Composite Index
6917 ISMMANPMI_mva365 Institute of Supply Managment PMI Composite Index 365 Day MA
6918 ISMMANPMI_mva200 Institute of Supply Managment PMI Composite Index 200 Day MA
6919 ISMMANPMI_mva050 Institute of Supply Managment PMI Composite Index 50 Day MA
6922 MULTPLSP500PERATIOMONTH_YoY5 S&P 500 TTM P/E 5 Year over 5 Year
6927 MULTPLSP500PERATIOMONTH_mva365 S&P 500 TTM P/E 365 Day MA
6928 MULTPLSP500PERATIOMONTH_mva200 S&P 500 TTM P/E 200 Day MA
6936 MULTPLSP500SALESQUARTER_Log Log of S&P 500 TTM Sales (Not Inflation Adjusted)
6937 MULTPLSP500SALESQUARTER_mva365 S&P 500 TTM Sales (Not Inflation Adjusted) 365 Day MA
6938 MULTPLSP500SALESQUARTER_mva200 S&P 500 TTM Sales (Not Inflation Adjusted) 200 Day MA
6939 MULTPLSP500SALESQUARTER_mva050 S&P 500 TTM Sales (Not Inflation Adjusted) 50 Day MA
6941 MULTPLSP500DIVYIELDMONTH_YoY4 S&P 500 Dividend Yield by Month 4 Year over 4 Year
6943 MULTPLSP500DIVYIELDMONTH_Smooth Savitsky-Golay Smoothed (p=3, n=365) S&P 500 Dividend Yield by Month
6945 MULTPLSP500DIVYIELDMONTH_SmoothDer Derivative of Smoothed S&P 500 Dividend Yield by Month
6957 MULTPLSP500DIVMONTH_mva365 S&P 500 Dividend by Month (Inflation Adjusted) 365 Day MA
6960 CHRISCMEHG1_YoY Copper Futures, Continuous Contract #1 (HG1) (Front Month) Year over Year
6966 CHRISCMEHG1_Log Log of Copper Futures, Continuous Contract #1 (HG1) (Front Month)
6967 CHRISCMEHG1_mva365 Copper Futures, Continuous Contract #1 (HG1) (Front Month) 365 Day MA
6968 CHRISCMEHG1_mva200 Copper Futures, Continuous Contract #1 (HG1) (Front Month) 200 Day MA
6969 CHRISCMEHG1_mva050 Copper Futures, Continuous Contract #1 (HG1) (Front Month) 50 Day MA
6970 WWDIWLDISAIRGOODMTK1_YoY Air transport, freight Year over Year
6971 WWDIWLDISAIRGOODMTK1_YoY4 Air transport, freight 4 Year over 4 Year
6976 WWDIWLDISAIRGOODMTK1_Log Log of Air transport, freight
6977 WWDIWLDISAIRGOODMTK1_mva365 Air transport, freight 365 Day MA
6978 WWDIWLDISAIRGOODMTK1_mva200 Air transport, freight 200 Day MA
6979 WWDIWLDISAIRGOODMTK1_mva050 Air transport, freight 50 Day MA
6983 LBMAGOLD.USD_AM_Smooth Savitsky-Golay Smoothed (p=3, n=365)
6987 LBMAGOLD.USD_AM_mva365 365 Day MA
6993 LBMAGOLD.USD_PM_Smooth Savitsky-Golay Smoothed (p=3, n=365)
6996 LBMAGOLD.USD_PM_Log Log of
6997 LBMAGOLD.USD_PM_mva365 365 Day MA
7003 LBMAGOLD.GBP_AM_Smooth Savitsky-Golay Smoothed (p=3, n=365)
7005 LBMAGOLD.GBP_AM_SmoothDer Derivative of Smoothed
7007 LBMAGOLD.GBP_AM_mva365 365 Day MA
7013 LBMAGOLD.GBP_PM_Smooth Savitsky-Golay Smoothed (p=3, n=365)
7015 LBMAGOLD.GBP_PM_SmoothDer Derivative of Smoothed
7017 LBMAGOLD.GBP_PM_mva365 365 Day MA
7023 LBMAGOLD.EURO_AM_Smooth Savitsky-Golay Smoothed (p=3, n=365)
7027 LBMAGOLD.EURO_AM_mva365 365 Day MA
7033 LBMAGOLD.EURO_PM_Smooth Savitsky-Golay Smoothed (p=3, n=365)
7037 LBMAGOLD.EURO_PM_mva365 365 Day MA
7040 PETA103600001M_YoY U.S. Total Gasoline Retail Sales by Refiners, Monthly Year over Year
7041 PETA103600001M_YoY4 U.S. Total Gasoline Retail Sales by Refiners, Monthly 4 Year over 4 Year
7042 PETA103600001M_YoY5 U.S. Total Gasoline Retail Sales by Refiners, Monthly 5 Year over 5 Year
7046 PETA103600001M_Log Log of U.S. Total Gasoline Retail Sales by Refiners, Monthly
7047 PETA103600001M_mva365 U.S. Total Gasoline Retail Sales by Refiners, Monthly 365 Day MA
7048 PETA103600001M_mva200 U.S. Total Gasoline Retail Sales by Refiners, Monthly 200 Day MA
7049 PETA103600001M_mva050 U.S. Total Gasoline Retail Sales by Refiners, Monthly 50 Day MA
7050 PETA123600001M_YoY U.S. Regular Gasoline Retail Sales by Refiners, Monthly Year over Year
7051 PETA123600001M_YoY4 U.S. Regular Gasoline Retail Sales by Refiners, Monthly 4 Year over 4 Year
7056 PETA123600001M_Log Log of U.S. Regular Gasoline Retail Sales by Refiners, Monthly
7057 PETA123600001M_mva365 U.S. Regular Gasoline Retail Sales by Refiners, Monthly 365 Day MA
7058 PETA123600001M_mva200 U.S. Regular Gasoline Retail Sales by Refiners, Monthly 200 Day MA
7059 PETA123600001M_mva050 U.S. Regular Gasoline Retail Sales by Refiners, Monthly 50 Day MA
7060 PETA143B00001M_YoY U.S. Midgrade Gasoline Retail Sales by Refiners, Monthly Year over Year
7061 PETA143B00001M_YoY4 U.S. Midgrade Gasoline Retail Sales by Refiners, Monthly 4 Year over 4 Year
7062 PETA143B00001M_YoY5 U.S. Midgrade Gasoline Retail Sales by Refiners, Monthly 5 Year over 5 Year
7066 PETA143B00001M_Log Log of U.S. Midgrade Gasoline Retail Sales by Refiners, Monthly
7067 PETA143B00001M_mva365 U.S. Midgrade Gasoline Retail Sales by Refiners, Monthly 365 Day MA
7068 PETA143B00001M_mva200 U.S. Midgrade Gasoline Retail Sales by Refiners, Monthly 200 Day MA
7069 PETA143B00001M_mva050 U.S. Midgrade Gasoline Retail Sales by Refiners, Monthly 50 Day MA
7070 PETA133B00001M_YoY U.S. Premium Gasoline Bulk Sales (Volume) by Refiners, Monthly Year over Year
7076 PETA133B00001M_Log Log of U.S. Premium Gasoline Bulk Sales (Volume) by Refiners, Monthly
7077 PETA133B00001M_mva365 U.S. Premium Gasoline Bulk Sales (Volume) by Refiners, Monthly 365 Day MA
7078 PETA133B00001M_mva200 U.S. Premium Gasoline Bulk Sales (Volume) by Refiners, Monthly 200 Day MA
7079 PETA133B00001M_mva050 U.S. Premium Gasoline Bulk Sales (Volume) by Refiners, Monthly 50 Day MA
7081 TOTALOGNRPUSM_YoY4 Crude Oil and Natural Gas Rotary Rigs in Operation, Total, Monthly 4 Year over 4 Year
7085 TOTALOGNRPUSM_SmoothDer Derivative of Smoothed Crude Oil and Natural Gas Rotary Rigs in Operation, Total, Monthly
7091 TOTALPANRPUSM_YoY4 Crude Oil Rotary Rigs in Operation, Monthly 4 Year over 4 Year
7095 TOTALPANRPUSM_SmoothDer Derivative of Smoothed Crude Oil Rotary Rigs in Operation, Monthly
7101 TOTALNGNRPUSM_YoY4 Natural Gas Rotary Rigs in Operation, Monthly 4 Year over 4 Year
7105 TOTALNGNRPUSM_SmoothDer Derivative of Smoothed Natural Gas Rotary Rigs in Operation, Monthly
7110 BKRTotal_YoY Total Rig Count Year over Year
7111 BKRTotal_YoY4 Total Rig Count 4 Year over 4 Year
7116 BKRTotal_Log Log of Total Rig Count
7117 BKRTotal_mva365 Total Rig Count 365 Day MA
7118 BKRTotal_mva200 Total Rig Count 200 Day MA
7119 BKRTotal_mva050 Total Rig Count 50 Day MA
7120 BKRGas_YoY Gas Rig Count Year over Year
7121 BKRGas_YoY4 Gas Rig Count 4 Year over 4 Year
7126 BKRGas_Log Log of Gas Rig Count
7127 BKRGas_mva365 Gas Rig Count 365 Day MA
7128 BKRGas_mva200 Gas Rig Count 200 Day MA
7129 BKRGas_mva050 Gas Rig Count 50 Day MA
7130 BKROil_YoY Oil Rig Count Year over Year
7131 BKROil_YoY4 Oil Rig Count 4 Year over 4 Year
7136 BKROil_Log Log of Oil Rig Count
7137 BKROil_mva365 Oil Rig Count 365 Day MA
7138 BKROil_mva200 Oil Rig Count 200 Day MA
7139 BKROil_mva050 Oil Rig Count 50 Day MA
7140 FARMINCOME_YoY Net Farm Income Year over Year
7141 FARMINCOME_YoY4 Net Farm Income 4 Year over 4 Year
7146 FARMINCOME_Log Log of Net Farm Income
7147 FARMINCOME_mva365 Net Farm Income 365 Day MA
7148 FARMINCOME_mva200 Net Farm Income 200 Day MA
7149 FARMINCOME_mva050 Net Farm Income 50 Day MA
7152 OPEARNINGSPERSHARE_YoY5 Operating Earnings per Share 5 Year over 5 Year
7153 OPEARNINGSPERSHARE_Smooth Savitsky-Golay Smoothed (p=3, n=365) Operating Earnings per Share
7155 OPEARNINGSPERSHARE_SmoothDer Derivative of Smoothed Operating Earnings per Share
7156 OPEARNINGSPERSHARE_Log Log of Operating Earnings per Share
7157 OPEARNINGSPERSHARE_mva365 Operating Earnings per Share 365 Day MA
7158 OPEARNINGSPERSHARE_mva200 Operating Earnings per Share 200 Day MA
7159 OPEARNINGSPERSHARE_mva050 Operating Earnings per Share 50 Day MA
7160 AREARNINGSPERSHARE_YoY As-Reported Earnings per Share Year over Year
7162 AREARNINGSPERSHARE_YoY5 As-Reported Earnings per Share 5 Year over 5 Year
7165 AREARNINGSPERSHARE_SmoothDer Derivative of Smoothed As-Reported Earnings per Share
7166 AREARNINGSPERSHARE_Log Log of As-Reported Earnings per Share
7169 AREARNINGSPERSHARE_mva050 As-Reported Earnings per Share 50 Day MA
7173 CASHDIVIDENDSPERSHR_Smooth Savitsky-Golay Smoothed (p=3, n=365) Cash Dividends per Share
7176 CASHDIVIDENDSPERSHR_Log Log of Cash Dividends per Share
7177 CASHDIVIDENDSPERSHR_mva365 Cash Dividends per Share 365 Day MA
7178 CASHDIVIDENDSPERSHR_mva200 Cash Dividends per Share 200 Day MA
7179 CASHDIVIDENDSPERSHR_mva050 Cash Dividends per Share 50 Day MA
7183 SALESPERSHR_Smooth Savitsky-Golay Smoothed (p=3, n=365) Sales per Share
7185 SALESPERSHR_SmoothDer Derivative of Smoothed Sales per Share
7186 SALESPERSHR_Log Log of Sales per Share
7187 SALESPERSHR_mva365 Sales per Share 365 Day MA
7188 SALESPERSHR_mva200 Sales per Share 200 Day MA
7189 SALESPERSHR_mva050 Sales per Share 50 Day MA
7193 BOOKVALPERSHR_Smooth Savitsky-Golay Smoothed (p=3, n=365) Book value per Share
7196 BOOKVALPERSHR_Log Log of Book value per Share
7197 BOOKVALPERSHR_mva365 Book value per Share 365 Day MA
7198 BOOKVALPERSHR_mva200 Book value per Share 200 Day MA
7199 BOOKVALPERSHR_mva050 Book value per Share 50 Day MA
7203 CAPEXPERSHR_Smooth Savitsky-Golay Smoothed (p=3, n=365) Cap ex per Share
7205 CAPEXPERSHR_SmoothDer Derivative of Smoothed Cap ex per Share
7206 CAPEXPERSHR_Log Log of Cap ex per Share
7207 CAPEXPERSHR_mva365 Cap ex per Share 365 Day MA
7208 CAPEXPERSHR_mva200 Cap ex per Share 200 Day MA
7209 CAPEXPERSHR_mva050 Cap ex per Share 50 Day MA
7212 PRICE_YoY5 Price 5 Year over 5 Year
7213 PRICE_Smooth Savitsky-Golay Smoothed (p=3, n=365) Price
7216 PRICE_Log Log of Price
7217 PRICE_mva365 Price 365 Day MA
7218 PRICE_mva200 Price 200 Day MA
7219 PRICE_mva050 Price 50 Day MA
7220 OPEARNINGSTTM_YoY TTM Operating Earnings Year over Year
7226 OPEARNINGSTTM_Log Log of TTM Operating Earnings
7229 OPEARNINGSTTM_mva050 TTM Operating Earnings 50 Day MA
7230 AREARNINGSTTM_YoY TTM Reported Earnings Year over Year
7236 AREARNINGSTTM_Log Log of TTM Reported Earnings
7239 AREARNINGSTTM_mva050 TTM Reported Earnings 50 Day MA
7240 FINRAMarginDebt_YoY Margin Debt Year over Year
7242 FINRAMarginDebt_YoY5 Margin Debt 5 Year over 5 Year
7246 FINRAMarginDebt_Log Log of Margin Debt
7248 FINRAMarginDebt_mva200 Margin Debt 200 Day MA
7249 FINRAMarginDebt_mva050 Margin Debt 50 Day MA
7250 FINRAFreeCreditMargin_YoY Free Credit Balances in Customers’ Securities Margin Accounts Year over Year
7255 FINRAFreeCreditMargin_SmoothDer Derivative of Smoothed Free Credit Balances in Customers’ Securities Margin Accounts
7260 OCCEquityVolume_YoY Equity Options Volume Year over Year
7266 OCCEquityVolume_Log Log of Equity Options Volume
7267 OCCEquityVolume_mva365 Equity Options Volume 365 Day MA
7268 OCCEquityVolume_mva200 Equity Options Volume 200 Day MA
7269 OCCEquityVolume_mva050 Equity Options Volume 50 Day MA
7270 OCCNonEquityVolume_YoY Non-Equity Options Volume Year over Year
7276 OCCNonEquityVolume_Log Log of Non-Equity Options Volume
7277 OCCNonEquityVolume_mva365 Non-Equity Options Volume 365 Day MA
7278 OCCNonEquityVolume_mva200 Non-Equity Options Volume 200 Day MA
7279 OCCNonEquityVolume_mva050 Non-Equity Options Volume 50 Day MA
7280 RSALESAGG_YoY Real Retail and Food Services Sales (RRSFS and RSALES) Year over Year
7282 RSALESAGG_YoY5 Real Retail and Food Services Sales (RRSFS and RSALES) 5 Year over 5 Year
7283 RSALESAGG_Smooth Savitsky-Golay Smoothed (p=3, n=365) Real Retail and Food Services Sales (RRSFS and RSALES)
7285 RSALESAGG_SmoothDer Derivative of Smoothed Real Retail and Food Services Sales (RRSFS and RSALES)
7288 RSALESAGG_mva200 Real Retail and Food Services Sales (RRSFS and RSALES) 200 Day MA
7295 BUSLOANS.minus.BUSLOANSNSA_SmoothDer Derivative of Smoothed Business Loans (Montlhy) SA - NSA
7296 BUSLOANS.minus.BUSLOANSNSA_Log Log of Business Loans (Montlhy) SA - NSA
7297 BUSLOANS.minus.BUSLOANSNSA_mva365 Business Loans (Montlhy) SA - NSA 365 Day MA
7298 BUSLOANS.minus.BUSLOANSNSA_mva200 Business Loans (Montlhy) SA - NSA 200 Day MA
7305 BUSLOANS.minus.BUSLOANSNSA.by.GDP_SmoothDer Derivative of Smoothed Business Loans (Montlhy) SA - NSA divided by GDP
7306 BUSLOANS.minus.BUSLOANSNSA.by.GDP_Log Log of Business Loans (Montlhy) SA - NSA divided by GDP
7308 BUSLOANS.minus.BUSLOANSNSA.by.GDP_mva200 Business Loans (Montlhy) SA - NSA divided by GDP 200 Day MA
7313 BUSLOANS.by.GDP_Smooth Savitsky-Golay Smoothed (p=3, n=365) Business Loans Normalized by GDP
7315 BUSLOANS.by.GDP_SmoothDer Derivative of Smoothed Business Loans Normalized by GDP
7323 BUSLOANS.INTEREST_Smooth Savitsky-Golay Smoothed (p=3, n=365) Business Loans (Monthly, SA) Adjusted Interest Burdens
7325 BUSLOANS.INTEREST_SmoothDer Derivative of Smoothed Business Loans (Monthly, SA) Adjusted Interest Burdens
7327 BUSLOANS.INTEREST_mva365 Business Loans (Monthly, SA) Adjusted Interest Burdens 365 Day MA
7328 BUSLOANS.INTEREST_mva200 Business Loans (Monthly, SA) Adjusted Interest Burdens 200 Day MA
7333 BUSLOANS.INTEREST.by.GDP_Smooth Savitsky-Golay Smoothed (p=3, n=365) Business Loans (Monthly, SA) Adjusted Interest Burden Divided by GDP
7335 BUSLOANS.INTEREST.by.GDP_SmoothDer Derivative of Smoothed Business Loans (Monthly, SA) Adjusted Interest Burden Divided by GDP
7337 BUSLOANS.INTEREST.by.GDP_mva365 Business Loans (Monthly, SA) Adjusted Interest Burden Divided by GDP 365 Day MA
7338 BUSLOANS.INTEREST.by.GDP_mva200 Business Loans (Monthly, SA) Adjusted Interest Burden Divided by GDP 200 Day MA
7345 BUSLOANSNSA.by.GDP_SmoothDer Derivative of Smoothed Business Loans Normalized by GDP
7355 TOTCI.by.GDP_SmoothDer Derivative of Smoothed Business Loans (Weekly, SA) Normalized by GDP
7365 TOTCINSA.by.GDP_SmoothDer Derivative of Smoothed Business Loans (Weekly, NSA) Normalized by GDP
7373 TOTCINSA.INTEREST_Smooth Savitsky-Golay Smoothed (p=3, n=365) Business Loans (Weekly, NSA) Adjusted Interest Burdens
7375 TOTCINSA.INTEREST_SmoothDer Derivative of Smoothed Business Loans (Weekly, NSA) Adjusted Interest Burdens
7377 TOTCINSA.INTEREST_mva365 Business Loans (Weekly, NSA) Adjusted Interest Burdens 365 Day MA
7378 TOTCINSA.INTEREST_mva200 Business Loans (Weekly, NSA) Adjusted Interest Burdens 200 Day MA
7383 TOTCINSA.INTEREST.by.GDP_Smooth Savitsky-Golay Smoothed (p=3, n=365) Business Loans (weekly, NSA) Adjusted Interest Burden Divided by GDP
7385 TOTCINSA.INTEREST.by.GDP_SmoothDer Derivative of Smoothed Business Loans (weekly, NSA) Adjusted Interest Burden Divided by GDP
7387 TOTCINSA.INTEREST.by.GDP_mva365 Business Loans (weekly, NSA) Adjusted Interest Burden Divided by GDP 365 Day MA
7388 TOTCINSA.INTEREST.by.GDP_mva200 Business Loans (weekly, NSA) Adjusted Interest Burden Divided by GDP 200 Day MA
7390 W875RX1.by.GDP_YoY Real Personal Income Normalized by GDP Year over Year
7395 W875RX1.by.GDP_SmoothDer Derivative of Smoothed Real Personal Income Normalized by GDP
7400 A065RC1A027NBEA.by.GDP_YoY Personal Income (NSA) Normalized by GDP Year over Year
7405 A065RC1A027NBEA.by.GDP_SmoothDer Derivative of Smoothed Personal Income (NSA) Normalized by GDP
7410 PI.by.GDP_YoY Personal Income (SA) Normalized by GDP Year over Year
7413 PI.by.GDP_Smooth Savitsky-Golay Smoothed (p=3, n=365) Personal Income (SA) Normalized by GDP
7415 PI.by.GDP_SmoothDer Derivative of Smoothed Personal Income (SA) Normalized by GDP
7416 PI.by.GDP_Log Log of Personal Income (SA) Normalized by GDP
7421 A053RC1Q027SBEA.by.GDP_YoY4 National income: Corporate profits before tax (without IVA and CCAdj) Normalized by GDP 4 Year over 4 Year
7422 A053RC1Q027SBEA.by.GDP_YoY5 National income: Corporate profits before tax (without IVA and CCAdj) Normalized by GDP 5 Year over 5 Year
7430 CPROFIT.by.GDP_YoY National income: Corporate profits before tax (with IVA and CCAdj) Normalized by GDP Year over Year
7431 CPROFIT.by.GDP_YoY4 National income: Corporate profits before tax (with IVA and CCAdj) Normalized by GDP 4 Year over 4 Year
7435 CPROFIT.by.GDP_SmoothDer Derivative of Smoothed National income: Corporate profits before tax (with IVA and CCAdj) Normalized by GDP
7445 CONSUMERNSA.by.GDP_SmoothDer Derivative of Smoothed Consumer Loans Not Seasonally Adjusted divided by GDP
7446 CONSUMERNSA.by.GDP_Log Log of Consumer Loans Not Seasonally Adjusted divided by GDP
7449 CONSUMERNSA.by.GDP_mva050 Consumer Loans Not Seasonally Adjusted divided by GDP 50 Day MA
7452 RREACBM027NBOG.by.GDP_YoY5 Residental Real Estate Loans (Monthly, NSA) divided by GDP 5 Year over 5 Year
7453 RREACBM027NBOG.by.GDP_Smooth Savitsky-Golay Smoothed (p=3, n=365) Residental Real Estate Loans (Monthly, NSA) divided by GDP
7455 RREACBM027NBOG.by.GDP_SmoothDer Derivative of Smoothed Residental Real Estate Loans (Monthly, NSA) divided by GDP
7456 RREACBM027NBOG.by.GDP_Log Log of Residental Real Estate Loans (Monthly, NSA) divided by GDP
7459 RREACBM027NBOG.by.GDP_mva050 Residental Real Estate Loans (Monthly, NSA) divided by GDP 50 Day MA
7462 RREACBM027SBOG.by.GDP_YoY5 Residental Real Estate Loans (Monthly, SA) divided by GDP 5 Year over 5 Year
7463 RREACBM027SBOG.by.GDP_Smooth Savitsky-Golay Smoothed (p=3, n=365) Residental Real Estate Loans (Monthly, SA) divided by GDP
7465 RREACBM027SBOG.by.GDP_SmoothDer Derivative of Smoothed Residental Real Estate Loans (Monthly, SA) divided by GDP
7472 RREACBW027SBOG.by.GDP_YoY5 Residental Real Estate Loans (Weekly, SA) divided by GDP 5 Year over 5 Year
7473 RREACBW027SBOG.by.GDP_Smooth Savitsky-Golay Smoothed (p=3, n=365) Residental Real Estate Loans (Weekly, SA) divided by GDP
7475 RREACBW027SBOG.by.GDP_SmoothDer Derivative of Smoothed Residental Real Estate Loans (Weekly, SA) divided by GDP
7477 RREACBW027SBOG.by.GDP_mva365 Residental Real Estate Loans (Weekly, SA) divided by GDP 365 Day MA
7482 RREACBW027NBOG.by.GDP_YoY5 Residental Real Estate Loans (Weekly, NSA) divided by GDP 5 Year over 5 Year
7483 RREACBW027NBOG.by.GDP_Smooth Savitsky-Golay Smoothed (p=3, n=365) Residental Real Estate Loans (Weekly, NSA) divided by GDP
7485 RREACBW027NBOG.by.GDP_SmoothDer Derivative of Smoothed Residental Real Estate Loans (Weekly, NSA) divided by GDP
7486 RREACBW027NBOG.by.GDP_Log Log of Residental Real Estate Loans (Weekly, NSA) divided by GDP
7487 RREACBW027NBOG.by.GDP_mva365 Residental Real Estate Loans (Weekly, NSA) divided by GDP 365 Day MA
7489 RREACBW027NBOG.by.GDP_mva050 Residental Real Estate Loans (Weekly, NSA) divided by GDP 50 Day MA
7510 ASHMA.by.GDP_YoY Home Mortgages (Quarterly, NSA) divided by GDP Year over Year
7515 ASHMA.by.GDP_SmoothDer Derivative of Smoothed Home Mortgages (Quarterly, NSA) divided by GDP
7523 ASHMA.INTEREST_Smooth Savitsky-Golay Smoothed (p=3, n=365) Home Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens
7525 ASHMA.INTEREST_SmoothDer Derivative of Smoothed Home Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens
7527 ASHMA.INTEREST_mva365 Home Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens 365 Day MA
7528 ASHMA.INTEREST_mva200 Home Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens 200 Day MA
7529 ASHMA.INTEREST_mva050 Home Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens 50 Day MA
7533 ASHMA.INTEREST.by.GDP_Smooth Savitsky-Golay Smoothed (p=3, n=365) Home Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens Divided by GDP
7535 ASHMA.INTEREST.by.GDP_SmoothDer Derivative of Smoothed Home Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens Divided by GDP
7537 ASHMA.INTEREST.by.GDP_mva365 Home Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens Divided by GDP 365 Day MA
7538 ASHMA.INTEREST.by.GDP_mva200 Home Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens Divided by GDP 200 Day MA
7539 ASHMA.INTEREST.by.GDP_mva050 Home Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens Divided by GDP 50 Day MA
7545 CONSUMERNSA.INTEREST_SmoothDer Derivative of Smoothed Consumer Loans (Not Seasonally Adjusted) Interest Burdens
7546 CONSUMERNSA.INTEREST_Log Log of Consumer Loans (Not Seasonally Adjusted) Interest Burdens
7547 CONSUMERNSA.INTEREST_mva365 Consumer Loans (Not Seasonally Adjusted) Interest Burdens 365 Day MA
7548 CONSUMERNSA.INTEREST_mva200 Consumer Loans (Not Seasonally Adjusted) Interest Burdens 200 Day MA
7549 CONSUMERNSA.INTEREST_mva050 Consumer Loans (Not Seasonally Adjusted) Interest Burdens 50 Day MA
7555 CONSUMERNSA.INTEREST.by.GDP_SmoothDer Derivative of Smoothed Consumer Loans (Not Seasonally Adjusted) Interest Burden Divided by GDP
7556 CONSUMERNSA.INTEREST.by.GDP_Log Log of Consumer Loans (Not Seasonally Adjusted) Interest Burden Divided by GDP
7557 CONSUMERNSA.INTEREST.by.GDP_mva365 Consumer Loans (Not Seasonally Adjusted) Interest Burden Divided by GDP 365 Day MA
7558 CONSUMERNSA.INTEREST.by.GDP_mva200 Consumer Loans (Not Seasonally Adjusted) Interest Burden Divided by GDP 200 Day MA
7559 CONSUMERNSA.INTEREST.by.GDP_mva050 Consumer Loans (Not Seasonally Adjusted) Interest Burden Divided by GDP 50 Day MA
7563 TOTLNNSA_Smooth Savitsky-Golay Smoothed (p=3, n=365) Total Loans Not Seasonally Adjusted (BUSLOANS+REALLNSA+CONSUMERNSA)
7565 TOTLNNSA_SmoothDer Derivative of Smoothed Total Loans Not Seasonally Adjusted (BUSLOANS+REALLNSA+CONSUMERNSA)
7566 TOTLNNSA_Log Log of Total Loans Not Seasonally Adjusted (BUSLOANS+REALLNSA+CONSUMERNSA)
7567 TOTLNNSA_mva365 Total Loans Not Seasonally Adjusted (BUSLOANS+REALLNSA+CONSUMERNSA) 365 Day MA
7568 TOTLNNSA_mva200 Total Loans Not Seasonally Adjusted (BUSLOANS+REALLNSA+CONSUMERNSA) 200 Day MA
7569 TOTLNNSA_mva050 Total Loans Not Seasonally Adjusted (BUSLOANS+REALLNSA+CONSUMERNSA) 50 Day MA
7573 TOTLNNSA.by.GDP_Smooth Savitsky-Golay Smoothed (p=3, n=365) Total Loans Not Seasonally Adjusted divided by GDP
7575 TOTLNNSA.by.GDP_SmoothDer Derivative of Smoothed Total Loans Not Seasonally Adjusted divided by GDP
7576 TOTLNNSA.by.GDP_Log Log of Total Loans Not Seasonally Adjusted divided by GDP
7583 TOTLNNSA.INTEREST_Smooth Savitsky-Golay Smoothed (p=3, n=365) Total Loans Not Seasonally Adjusted Interest Burdens
7585 TOTLNNSA.INTEREST_SmoothDer Derivative of Smoothed Total Loans Not Seasonally Adjusted Interest Burdens
7587 TOTLNNSA.INTEREST_mva365 Total Loans Not Seasonally Adjusted Interest Burdens 365 Day MA
7588 TOTLNNSA.INTEREST_mva200 Total Loans Not Seasonally Adjusted Interest Burdens 200 Day MA
7593 TOTLNNSA.INTEREST.by.GDP_Smooth Savitsky-Golay Smoothed (p=3, n=365) Total Loans Not Seasonally Adjusted Interest Burden Divided by GDP
7595 TOTLNNSA.INTEREST.by.GDP_SmoothDer Derivative of Smoothed Total Loans Not Seasonally Adjusted Interest Burden Divided by GDP
7597 TOTLNNSA.INTEREST.by.GDP_mva365 Total Loans Not Seasonally Adjusted Interest Burden Divided by GDP 365 Day MA
7598 TOTLNNSA.INTEREST.by.GDP_mva200 Total Loans Not Seasonally Adjusted Interest Burden Divided by GDP 200 Day MA
7602 WRESBAL.by.GDP_YoY5 Reserve Balances with Federal Reserve Banks Divided by GDP 5 Year over 5 Year
7603 WRESBAL.by.GDP_Smooth Savitsky-Golay Smoothed (p=3, n=365) Reserve Balances with Federal Reserve Banks Divided by GDP
7606 WRESBAL.by.GDP_Log Log of Reserve Balances with Federal Reserve Banks Divided by GDP
7609 WRESBAL.by.GDP_mva050 Reserve Balances with Federal Reserve Banks Divided by GDP 50 Day MA
7610 EXCSRESNW.by.GDP_YoY Excess Reserves of Depository Institutions Divided by GDP Year over Year
7612 EXCSRESNW.by.GDP_YoY5 Excess Reserves of Depository Institutions Divided by GDP 5 Year over 5 Year
7615 EXCSRESNW.by.GDP_SmoothDer Derivative of Smoothed Excess Reserves of Depository Institutions Divided by GDP
7635 SOFR99.minus.SOFR1_SmoothDer Derivative of Smoothed Secured Overnight Financing Rate: 99th Percentile - 1st Percentile
7641 EXPCH.minus.IMPCH_YoY4 U.S. Exports to China (FAS Basis) - U.S. Imports to China (Customs Basis) 4 Year over 4 Year
7642 EXPCH.minus.IMPCH_YoY5 U.S. Exports to China (FAS Basis) - U.S. Imports to China (Customs Basis) 5 Year over 5 Year
7645 EXPCH.minus.IMPCH_SmoothDer Derivative of Smoothed U.S. Exports to China (FAS Basis) - U.S. Imports to China (Customs Basis)
7646 EXPCH.minus.IMPCH_Log Log of U.S. Exports to China (FAS Basis) - U.S. Imports to China (Customs Basis)
7653 EXPMX.minus.IMPMX_Smooth Savitsky-Golay Smoothed (p=3, n=365)
7655 EXPMX.minus.IMPMX_SmoothDer Derivative of Smoothed
7656 EXPMX.minus.IMPMX_Log Log of
7659 EXPMX.minus.IMPMX_mva050 50 Day MA
7665 SRPSABSNNCB.by.GDP_SmoothDer Derivative of Smoothed Nonfinancial corporate business; security repurchase agreements; asset, Level (NSA) Divided by GDP
7666 SRPSABSNNCB.by.GDP_Log Log of Nonfinancial corporate business; security repurchase agreements; asset, Level (NSA) Divided by GDP
7675 ASTLL.by.GDP_SmoothDer Derivative of Smoothed All sectors; total loans; liability, Level (NSA) Divided by GDP
7696 ASFMA.by.ASTLL_Log Log of All sectors; total loans Divided by farm mortgages
7697 ASFMA.by.ASTLL_mva365 All sectors; total loans Divided by farm mortgages 365 Day MA
7698 ASFMA.by.ASTLL_mva200 All sectors; total loans Divided by farm mortgages 200 Day MA
7699 ASFMA.by.ASTLL_mva050 All sectors; total loans Divided by farm mortgages 50 Day MA
7703 ASFMA.INTEREST_Smooth Savitsky-Golay Smoothed (p=3, n=365) Farm Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens
7705 ASFMA.INTEREST_SmoothDer Derivative of Smoothed Farm Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens
7707 ASFMA.INTEREST_mva365 Farm Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens 365 Day MA
7708 ASFMA.INTEREST_mva200 Farm Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens 200 Day MA
7709 ASFMA.INTEREST_mva050 Farm Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens 50 Day MA
7713 ASFMA.INTEREST.by.GDP_Smooth Savitsky-Golay Smoothed (p=3, n=365) Farm Mortgages (Quarterly, NSA) Interest Burden Divided by GDP
7715 ASFMA.INTEREST.by.GDP_SmoothDer Derivative of Smoothed Farm Mortgages (Quarterly, NSA) Interest Burden Divided by GDP
7717 ASFMA.INTEREST.by.GDP_mva365 Farm Mortgages (Quarterly, NSA) Interest Burden Divided by GDP 365 Day MA
7718 ASFMA.INTEREST.by.GDP_mva200 Farm Mortgages (Quarterly, NSA) Interest Burden Divided by GDP 200 Day MA
7719 ASFMA.INTEREST.by.GDP_mva050 Farm Mortgages (Quarterly, NSA) Interest Burden Divided by GDP 50 Day MA
7720 FARMINCOME.by.GDP_YoY Farm Income (Annual, NSA) Divided by GDP Year over Year
7725 FARMINCOME.by.GDP_SmoothDer Derivative of Smoothed Farm Income (Annual, NSA) Divided by GDP
7732 BOGMBASE.by.GDP_YoY5 BOGMBASE Divided by GDP 5 Year over 5 Year
7750 ECBASSETS.by.EUNNGDP_YoY Central Bank Assets for Euro Area (11-19 Countries) Divided by GDP Year over Year
7755 ECBASSETS.by.EUNNGDP_SmoothDer Derivative of Smoothed Central Bank Assets for Euro Area (11-19 Countries) Divided by GDP
7756 ECBASSETS.by.EUNNGDP_Log Log of Central Bank Assets for Euro Area (11-19 Countries) Divided by GDP
7759 ECBASSETS.by.EUNNGDP_mva050 Central Bank Assets for Euro Area (11-19 Countries) Divided by GDP 50 Day MA
7763 DGS30TO10_Smooth Savitsky-Golay Smoothed (p=3, n=365) Yield Curve, 30 and 10 Year Treasury (DGS30-DGS10)
7766 DGS30TO10_Log Log of Yield Curve, 30 and 10 Year Treasury (DGS30-DGS10)
7773 DGS10TO1_Smooth Savitsky-Golay Smoothed (p=3, n=365) Yield Curve, 10 and 1 Year Treasury (DGS10-DGS1)
7775 DGS10TO1_SmoothDer Derivative of Smoothed Yield Curve, 10 and 1 Year Treasury (DGS10-DGS1)
7776 DGS10TO1_Log Log of Yield Curve, 10 and 1 Year Treasury (DGS10-DGS1)
7783 DGS10TO2_Smooth Savitsky-Golay Smoothed (p=3, n=365) Yield Curve, 10 and 2 Year Treasury (DGS10-DGS2)
7785 DGS10TO2_SmoothDer Derivative of Smoothed Yield Curve, 10 and 2 Year Treasury (DGS10-DGS2)
7786 DGS10TO2_Log Log of Yield Curve, 10 and 2 Year Treasury (DGS10-DGS2)
7793 DGS10TOTB3MS_Smooth Savitsky-Golay Smoothed (p=3, n=365) Yield Curve, 10 and 3 Month Treasury (DGS10-TB3MS)
7795 DGS10TOTB3MS_SmoothDer Derivative of Smoothed Yield Curve, 10 and 3 Month Treasury (DGS10-TB3MS)
7796 DGS10TOTB3MS_Log Log of Yield Curve, 10 and 3 Month Treasury (DGS10-TB3MS)
7803 DGS10TODTB3_Smooth Savitsky-Golay Smoothed (p=3, n=365) Yield Curve, 10 and 3 Month Treasury (DGS10-DTB3)
7805 DGS10TODTB3_SmoothDer Derivative of Smoothed Yield Curve, 10 and 3 Month Treasury (DGS10-DTB3)
7806 DGS10TODTB3_Log Log of Yield Curve, 10 and 3 Month Treasury (DGS10-DTB3)
7820 LNU03000000BYPOPTHM_YoY Unemployment level (NSA) / Population Year over Year
7827 LNU03000000BYPOPTHM_mva365 Unemployment level (NSA) / Population 365 Day MA
7828 LNU03000000BYPOPTHM_mva200 Unemployment level (NSA) / Population 200 Day MA
7830 UNEMPLOYBYPOPTHM_YoY Unemployment level, seasonally adjusted / Population Year over Year
7831 UNEMPLOYBYPOPTHM_YoY4 Unemployment level, seasonally adjusted / Population 4 Year over 4 Year
7833 UNEMPLOYBYPOPTHM_Smooth Savitsky-Golay Smoothed (p=3, n=365) Unemployment level, seasonally adjusted / Population
7835 UNEMPLOYBYPOPTHM_SmoothDer Derivative of Smoothed Unemployment level, seasonally adjusted / Population
7836 UNEMPLOYBYPOPTHM_Log Log of Unemployment level, seasonally adjusted / Population
7837 UNEMPLOYBYPOPTHM_mva365 Unemployment level, seasonally adjusted / Population 365 Day MA
7838 UNEMPLOYBYPOPTHM_mva200 Unemployment level, seasonally adjusted / Population 200 Day MA
7839 UNEMPLOYBYPOPTHM_mva050 Unemployment level, seasonally adjusted / Population 50 Day MA
7840 NPPTTLBYPOPTHM_YoY ADP Private Employment / Population Year over Year
7845 NPPTTLBYPOPTHM_SmoothDer Derivative of Smoothed ADP Private Employment / Population
7851 U6toU3_YoY4 U6RATE minums UNRATE 4 Year over 4 Year
7853 U6toU3_Smooth Savitsky-Golay Smoothed (p=3, n=365) U6RATE minums UNRATE
7856 U6toU3_Log Log of U6RATE minums UNRATE
7857 U6toU3_mva365 U6RATE minums UNRATE 365 Day MA
7858 U6toU3_mva200 U6RATE minums UNRATE 200 Day MA
7859 U6toU3_mva050 U6RATE minums UNRATE 50 Day MA
7867 CHRISCMEHG1.by.PPIACO_mva365 Copper, $/lb, Normalized by commodities producer price index 365 Day MA
7870 CHRISCMEHG1.by.CPIAUCSL_YoY Copper, $/lb, Normalized by consumer price index Year over Year
7875 CHRISCMEHG1.by.CPIAUCSL_SmoothDer Derivative of Smoothed Copper, $/lb, Normalized by consumer price index
7882 DCOILBRENTEU.by.PPIACO_YoY5 Crude Oil - Brent, $/bbl, Normalized by producer price index c.o. 5 Year over 5 Year
7883 DCOILBRENTEU.by.PPIACO_Smooth Savitsky-Golay Smoothed (p=3, n=365) Crude Oil - Brent, $/bbl, Normalized by producer price index c.o.
7885 DCOILBRENTEU.by.PPIACO_SmoothDer Derivative of Smoothed Crude Oil - Brent, $/bbl, Normalized by producer price index c.o.
7888 DCOILBRENTEU.by.PPIACO_mva200 Crude Oil - Brent, $/bbl, Normalized by producer price index c.o. 200 Day MA
7893 DCOILWTICO.by.PPIACO_Smooth Savitsky-Golay Smoothed (p=3, n=365) Crude Oil - WTI, $/bbl, Normalized by producer price index c.o.
7895 DCOILWTICO.by.PPIACO_SmoothDer Derivative of Smoothed Crude Oil - WTI, $/bbl, Normalized by producer price index c.o.
7896 DCOILWTICO.by.PPIACO_Log Log of Crude Oil - WTI, $/bbl, Normalized by producer price index c.o.
7898 DCOILWTICO.by.PPIACO_mva200 Crude Oil - WTI, $/bbl, Normalized by producer price index c.o. 200 Day MA
7906 LBMAGOLD.USD_PM.by.PPIACO_Log Log of Gold, USD PM/Troy Ounce, Normalized by commodities producer price index
7907 LBMAGOLD.USD_PM.by.PPIACO_mva365 Gold, USD PM/Troy Ounce, Normalized by commodities producer price index 365 Day MA
7916 LBMAGOLD.USD_PM.by.CPIAUCSL_Log Log of Gold, USD/Troy OUnce, Normalized by consumer price index
7917 LBMAGOLD.USD_PM.by.CPIAUCSL_mva365 Gold, USD/Troy OUnce, Normalized by consumer price index 365 Day MA
7926 LBMAGOLD.USD_PM.by.GDP_Log Log of Gold, USD/Troy OUnce, Normalized by GDP
7927 LBMAGOLD.USD_PM.by.GDP_mva365 Gold, USD/Troy OUnce, Normalized by GDP 365 Day MA
7931 GDP.by.GDPDEF_YoY4 Nominal GDP Normalized by GDP def 4 Year over 4 Year
7936 GDP.by.GDPDEF_Log Log of Nominal GDP Normalized by GDP def
7937 GDP.by.GDPDEF_mva365 Nominal GDP Normalized by GDP def 365 Day MA
7938 GDP.by.GDPDEF_mva200 Nominal GDP Normalized by GDP def 200 Day MA
7939 GDP.by.GDPDEF_mva050 Nominal GDP Normalized by GDP def 50 Day MA
7942 GSG.Close.by.GDPDEF_YoY5 GSCI Commodity-Indexed Trust, Normalized by GDP def 5 Year over 5 Year
7943 GSG.Close.by.GDPDEF_Smooth Savitsky-Golay Smoothed (p=3, n=365) GSCI Commodity-Indexed Trust, Normalized by GDP def
7945 GSG.Close.by.GDPDEF_SmoothDer Derivative of Smoothed GSCI Commodity-Indexed Trust, Normalized by GDP def
7948 GSG.Close.by.GDPDEF_mva200 GSCI Commodity-Indexed Trust, Normalized by GDP def 200 Day MA
7953 GSG.Close.by.GSPC.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365) GSCI Commodity-Indexed Trust, Normalized by S&P 500
7955 GSG.Close.by.GSPC.Close_SmoothDer Derivative of Smoothed GSCI Commodity-Indexed Trust, Normalized by S&P 500
7967 GDPBYPOPTHM_mva365 GDP/Population 365 Day MA
7968 GDPBYPOPTHM_mva200 GDP/Population 200 Day MA
7977 GDPBYCPIAUCSL_mva365 GDP divided by CPI 365 Day MA
7987 GDPBYCPIAUCSLBYPOPTHM_mva365 GDP divided by CPI/Population 365 Day MA
7993 GSPC.CloseBYMDY.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365) GSPC by MDY
7997 GSPC.CloseBYMDY.Close_mva365 GSPC by MDY 365 Day MA
7998 GSPC.CloseBYMDY.Close_mva200 GSPC by MDY 200 Day MA
7999 GSPC.CloseBYMDY.Close_mva050 GSPC by MDY 50 Day MA
8002 QQQ.CloseBYMDY.Close_YoY5 QQQ by MDY 5 Year over 5 Year
8007 QQQ.CloseBYMDY.Close_mva365 QQQ by MDY 365 Day MA
8008 QQQ.CloseBYMDY.Close_mva200 QQQ by MDY 200 Day MA
8009 QQQ.CloseBYMDY.Close_mva050 QQQ by MDY 50 Day MA
8013 GSPC.DailySwing_Smooth Savitsky-Golay Smoothed (p=3, n=365) S&P 500 (^GSPC) Daily Swing: (High - Low) / Open
8015 GSPC.DailySwing_SmoothDer Derivative of Smoothed S&P 500 (^GSPC) Daily Swing: (High - Low) / Open
8016 GSPC.DailySwing_Log Log of S&P 500 (^GSPC) Daily Swing: (High - Low) / Open
8022 GSPC.Open.by.GDPDEF_YoY5 S&P 500 (^GSPC) Open divided by GDP deflator 5 Year over 5 Year
8027 GSPC.Open.by.GDPDEF_mva365 S&P 500 (^GSPC) Open divided by GDP deflator 365 Day MA
8028 GSPC.Open.by.GDPDEF_mva200 S&P 500 (^GSPC) Open divided by GDP deflator 200 Day MA
8032 GSPC.Close.by.GDPDEF_YoY5 S&P 500 (^GSPC) Close divided by GDP deflator 5 Year over 5 Year
8037 GSPC.Close.by.GDPDEF_mva365 S&P 500 (^GSPC) Close divided by GDP deflator 365 Day MA
8038 GSPC.Close.by.GDPDEF_mva200 S&P 500 (^GSPC) Close divided by GDP deflator 200 Day MA
8045 HNFSUSNSA.minus.HSN1FNSA_SmoothDer Derivative of Smoothed Houses for sale - houses sold
8048 HNFSUSNSA.minus.HSN1FNSA_mva200 Houses for sale - houses sold 200 Day MA
8052 MSPUS.times.HOUST_YoY5 New privately owned units start times median price 5 Year over 5 Year
8062 HOUST.div.POPTHM_YoY5 Housing starts divided by U.S. population 5 Year over 5 Year
8070 MSPUS.times.HNFSUSNSA_YoY New privately owned 1-family units for sale times median price Year over Year
8075 MSPUS.times.HNFSUSNSA_SmoothDer Derivative of Smoothed New privately owned 1-family units for sale times median price
8076 MSPUS.times.HNFSUSNSA_Log Log of New privately owned 1-family units for sale times median price
8078 MSPUS.times.HNFSUSNSA_mva200 New privately owned 1-family units for sale times median price 200 Day MA
8079 MSPUS.times.HNFSUSNSA_mva050 New privately owned 1-family units for sale times median price 50 Day MA
8080 MSPUS.times.HSN1FNSA.plusEXHOSLUSM495S_YoY Median home price times new and existing houses sold Year over Year
8090 MSPUS.times.HSN1FNSA.plusEXHOSLUSM495S.by.GDP_YoY New and existing home sales volume Year over Year
8100 TOTLNNSA.PLUS.WRESBAL Total Loans Plus All Reserves (TOTLNNSA + WRESBAL)
8101 TOTLLNSA.PLUS.WRESBAL Total Loans Plus All Reserves (TOTLLNSA + WRESBAL)
8108 MULTPLSP500PERATIOMONTH_Mean S&P 500 TTM P/E Average (Excludes Values Greater Than 50)

Equities

Equity indexes normalized by GDP

## Scale for 'y' is already present. Adding another scale for 'y', which will
## replace the existing scale.

The last two years compare favorably with the period around the late 1950’s. Need to dig into this one.

datay <- "GSPC.Close"
ylim <- c(2000, d.GSPC.max)
my.data <- plotSimilarPeriods(df.data, dfRecession, df.symbols, datay, ylim, i.window = 60)
my.data[[1]]

Look at how the different segments of the market move

datay <- "GSPC.CloseBYMDY.Close_YoY"
ylim <- c(-50, 75)
dtStart = as.Date('1980-01-01')
plotSingle(dfRecession, df.data, "date", datay, getPlotTitle(df.symbols, datay), "Date", 
            getPlotYLabel(df.symbols, datay), c(dtStart, Sys.Date()), ylim, TRUE)

datay <- "GSPC.CloseBYMDY.Close"
ylim <- c(0, 20)
dtStart = as.Date('1980-01-01')
plotSingle(dfRecession, df.data, "date", datay, getPlotTitle(df.symbols, datay), "Date", 
            getPlotYLabel(df.symbols, datay), c(dtStart, Sys.Date()), ylim, TRUE)

S&P 500 Normalized moving average

Look at moving average relationship by dividing the S&P 500 open price by the 200 day SMA.

datay <- "GSPC.Open_mva200_Norm"
ylim <- c(50, 125)
dt.start = as.Date('2008-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dt.start)

Crossovers

Look at the 50 DMA versus 200 DMA, often used as a technical indicator of market direction.

datay <- "GSPC.Open_mva050_mva200"
ylim <- c(-300, 300)
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStartBackTest)

datay <- "GSPC.Open_mva050_mva200_sig "
ylim <- c(0.0, 1.0)
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStartBackTest)

S&P 500 TTM P/E

Take a look at some of the earnings trends from SilverBlatt’s sheet.

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## * ...

Take a longer look back at as-reported and operating earnings

Market prices can out-run earnings so take a look at price to earnings.

Focus on some of the more recent activity

S&P 500 Sales

datay <- "MULTPLSP500SALESQUARTER"
ylim <- c(500, 2000)
dt.start <- as.Date('1999-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dt.start)

datay <- "MULTPLSP500SALESQUARTER"
ylim <- c(500, 2000)
dt.start = as.Date('2001-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dt.start)

Unit Profits

The series peaks in the middle of a bull market.

S&P 500 dividends

12-month real dividend per share inflation adjusted November, 2018 dollars. Data courtesy Standard & Poor’s and Robert Shiller.

https://www.quandl.com/data/MULTPL/SP500_DIV_MONTH-S-P-500-Dividend-by-Month

Evaluate year over year dividend growth.

Real value dividend growth.

datay <- "MULTPLSP500DIVMONTH_YoY"
ylim <- c(-40, 20)
dtStart = as.Date('2001-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart, b.percentile = FALSE)

S&P 500 dividend yield (12 month dividend per share)/price. Yields following September 2018 (including the current yield) are estimated based on 12 month dividends through September 2018, as reported by S&P. Sources: Standard & Poor’s for current S&P 500 Dividend Yield. Robert Shiller and his book Irrational Exuberance for historic S&P 500 Dividend Yields.

https://www.quandl.com/data/MULTPL/SP500_DIV_YIELD_MONTH-S-P-500-Dividend-Yield-by-Month

datay <- "MULTPLSP500DIVYIELDMONTH"
ylim <- c(0, 12)
dtStart = as.Date('1950-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart, b.percentile = FALSE)

datay <- "MULTPLSP500DIVYIELDMONTH"
ylim <- c(1, 4)
dtStart = as.Date('2001-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart, b.percentile = FALSE)

S&P 500 Volume

The log of the S&P volume has some interesting patterns, but nothing that seems to help with a recession indicator.

That is one spiky data series. Not sure there is a lot to help us here.

Russell 2000

Take a look at recent activity in the small cap market.

S&P 500 to Rusell 2000

Thirty day movement

Correlation

## Warning in max.default(structure(numeric(0), class = "Date"),
## structure(numeric(0), class = "Date"), : no non-missing arguments to max;
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## Warning in min.default(structure(numeric(0), class = "Date"),
## structure(numeric(0), class = "Date"), : no non-missing arguments to min;
## returning Inf

S&P 500 to MDY (Mid-cap) 2000 Correlation

datay1 <- "RLG.Open"
ylim1 <- c(0, 2500)

datay2 <- "MDY.Open"
ylim2 <- c(0, 500)

dtStart <- as.Date("1jan2003","%d%b%Y")

w <- 30
corrName <-
  calcRollingCorr(dfRecession,
                  df.data,
                  df.symbols,
                  datay1,
                  ylim1,
                  datay2,
                  ylim2,
                  w,
                  dtStart)
## Warning in max.default(structure(numeric(0), class = "Date"),
## structure(numeric(0), class = "Date"), : no non-missing arguments to max;
## returning -Inf
## Warning in min.default(structure(numeric(0), class = "Date"),
## structure(numeric(0), class = "Date"), : no non-missing arguments to min;
## returning Inf

Dividend Stocks

This is an interesting series, they should perform better through the recessions. Unfortunately they are short lived so there is not much data so this is more of a place holder for now.

datay <- "NOBL.Open"
ylim <- c(40, 110)
dt.start <- as.Date('2014-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dt.start)

Margin and option data

NYSE Margin Debt

Taking a look at margin debt. NYXDATA stopped providing NYSE margin debt data on Dec 2017. Data is available from FINRA, but it includes more accounts than the data did for NYXdata. I stitched togeter the data sets: data after Jan 2010 include NYSE+Others, data prior is just NYSE account data scaled up to match the FINRA data.

It tends to creep up when there is a frenzy in the stock market.

datay <- "FINRAMarginDebt_Log"
ylim <- c(5, 15)
plotSingleQuick(dfRecession, df.data, datay, ylim)

Take a close look at recent activity

Sometimes it is more helpful to view year over year growth.

More near-term trend.

Take a look at some of the correlations

datay1 <- "FINRAMarginDebt_YoY"
ylim1 <- c(-100, 100)

datay2 <- "GSPC.Close_YoY"
ylim2 <- c(-100, 100)

dtStart <- as.Date("1jan1995","%d%b%Y")

w <- 90
corrName <-
  calcRollingCorr(dfRecession,
                  df.data,
                  df.symbols,
                  datay1,
                  ylim1,
                  datay2,
                  ylim2,
                  w,
                  dtStart)

Comparison to the Russell 2000

datay1 <- "FINRAMarginDebt_YoY"
ylim1 <- c(-100, 100)

datay2 <- "RLG.Close_YoY"
ylim2 <- c(-100, 100)

dtStart <- as.Date("1jan1995","%d%b%Y")

w <- 90
corrName <-
  calcRollingCorr(dfRecession,
                  df.data,
                  df.symbols,
                  datay1,
                  ylim1,
                  datay2,
                  ylim2,
                  w,
                  dtStart)

OCC Options Volumes

See what is happening with the options volumes for equities. (From: https://www.theocc.com/webapps/historical-volume-query)

Looks like options on non-equity co-occurs with peaks/troughs?.

Market Volatility

Take a look at some of the indications of market volatility

CBOE VIX

As markets become complacent (low VIX) and high values, peaks often occur.

Compare the VIX to some of the ETF’s out there.

There

Not much predictive in VIX, take a quick look at the smoothed derivative.

S&P Daily Swings

Daily changes in the S&P should correlate well with the VIX.

More of a correlating series than a predictor.

Employment and payrolls

Unemployment rates

Unemployment rates will probably be useful, let’s take a look at the U-3. The data is a little noisy so there is also a smoothed version plotted. There seems to be a relationship between the unemployment rate and the recessions, but it could be a lagging indicator. This will be explored a little bit more later.

Suggested by Charlie and a Wealthian video the 12 month-MA might be helpful to look at.

Looking at the unemployment rate, the eye is drawn to the rise and fall of the data, this suggests that the derivative might be helpful as well. The figure below shows the results, using a Savitzky-Golay FIR filter. It looks like the unemployment rate peaks in the middel of the recession. That peak might be a good buy signal.

Continuing Claims

A good measure of how much unemployment is growing.

Continued claims, also referred to as insured unemployment, is the number of people who have already filed an initial claim and who have experienced a week of unemployment and then filed a continued claim to claim benefits for that week of unemployment. Continued claims data are based on the week of unemployment, not the week when the initial claim was filed

https://fred.stlouisfed.org/series/CCNSA

A good measure of how much unemployment is growing

Initial Claims

A good measure of how much unemployment is growing.

An initial claim is a claim filed by an unemployed individual after a separation from an employer. The claim requests a determination of basic eligibility for the Unemployment Insurance program.

https://fred.stlouisfed.org/series/ICSA

Unemployment rates, year-over-year

Both the headline unemployment and U-6 number changes are similar. During the upswing on the cycle it does look like the headline number falls faster than U-6

The second derivative of the unemployment rate does have zero crossings near the middle point of a recession. This would make it a helpful buy signal for the trading strategy.

Unemployment rates, similar periods

Historically the last two years of record low unemployment appear most similar to the 1971-1973 time frame. Just before inflation took off.

Unemployment rates, U-6 and headline number.

Let’s also take a look at the total unemployed, U-6. It continues to fall as the headline number stabilizes as people return to the work force. An indicator the cycle is beginning to top out.

Difference between U6 and U3 to see how close the economy is getting to full employment.

Unemployment and market bottoms

## Scale for 'y' is already present. Adding another scale for 'y', which will
## replace the existing scale.

Initial jobless claims

We will also take a look at initial jobless claims, this should start to rise just before the unemployment rate.

It looks like the jobless claim tend to peak more towards the end of the recession. It does not seem to be as strong of a sell indicator as the U-3 rate.

Jobless claims have a seasonal component to them. One way to reduce this effect is to calculate year over year growth. That helps some, the peaks seem to be more closely aligned with the middle to end of recessions.

Take a closer look at recent data

## Warning: Removed 1 rows containing missing values (geom_text).
## Warning: Removed 1 rows containing missing values (geom_hline).

Take a look at the percentage of the population looking for work

A bit more recent trend

Unemployment Level

ADP data here. comes out before the official numbers.

Look at the year-over-year change in ADP.

ADP data divided by the population

Payrolls

Look at the BLS data on payrolls. Check the NSA series, then we will look at YoY data.

Hours worked

Sparked by an article at Mises (https://mises.org/wire/how-alexandria-ocasio-cortez-misunderstands-american-poverty), take a look at average weekly hours

The time series is pretty lumpy, plot the YoY change

A more recent look at average weekly hours of production

Industrial Production

Industrial production is also known to fall during an economic downturm, let’s take a look at some of the data from the FRED on industrial production. It does seem to peak prior to a recession so let’s smooth and look at the derivative as it might be a good indicator as well.

Industrial production over the last ten years or so

The derivative isn’t bad, but it sometimes crosses zeros well into a recession. That is less helpful as either a buy or sell indicator. A better measure might year over year (YoY) change.

The year over year change has a similar appearance. The low values at the beginning make the year over year values larger than the more recent values. Seems like it will rank low a reliable indicator.

datay1 <- "INDPRO_YoY"
ylim1 <- c(-20, 12)

datay2 <- "GSPC.Close_YoY"
ylim2 <- c(-100, 50)

dtStart <- as.Date("1jan1981","%d%b%Y")

w <- 360
corrName <- calcRollingCorr(dfRecession, df.data, df.symbols, datay1, ylim1, datay2, ylim2, w, dtStart)

Retail Sales

Retail sales, aggregate

Retail sales also change during recession. As the plot below shows, it seems to follow the trend of industrial production. It might be too strongly correlated to add much to the model. The will be examined in the correlation section.

The derivative of retail sales is a little more erratic than is was the industrial products. Looks like it might be helpful to include in the model as well.

Retail sales, aggregate year-over-year

Take a look at year-over-year changes

Retail sales and unemployment correlations

Let’s see how that looks on year over year basis. Interesting to compare to unemployment rates there appears to a correlation over the long term.

## Scale for 'y' is already present. Adding another scale for 'y', which will
## replace the existing scale.

There is some similarity. The rolling correlation shows the inverse relationship prior to a recession.

datay1 <- "RSALESAGG_YoY"
ylim1 <- c(-12.5, 12.5)

datay2 <- "UNEMPLOY_YoY"
ylim2 <- c(-30, 150)

dtStart <- as.Date("1jan1970","%d%b%Y")

w <- 180
corrName <- calcRollingCorr(dfRecession,df.data, df.symbols, datay1, ylim1, datay2, ylim2, w, dtStart)

Retail sales correlation and industrial production

Industrial production and retail sales look very similar so the plot below shows the 360 correlation. The corerlation does tend to fall around a recession, although 2008 was so bad that they both fell together. Not sure if it is that useful.

datay1 <- "INDPRO"
ylim1 <- c(40, 125)

datay2 <- "RSALESAGG"
ylim2 <- c(100000, 200000)

dtStart <- as.Date("1jan1981","%d%b%Y")

w <- 60
corrName <- calcRollingCorr(dfRecession, df.data, df.symbols, datay1, ylim1, datay2, ylim2, w, dtStart)

It is interesting to see the strong correlation; however, I suspect this is due to more to the shape of the trends. How do the YoY correlations look? They are a little less correlated, probably better to use in the machine learning later.

datay1 <- "INDPRO_YoY"
ylim1 <- c(-20, 20)

datay2 <- "RSALESAGG_YoY"
ylim2 <- c(-20, 20)

dtStart <- as.Date("1jan1981","%d%b%Y")

w <- 30
corrName <- calcRollingCorr(dfRecession, df.data, df.symbols, datay1, ylim1, datay2, ylim2, w, dtStart)

Advance Retail Sales

This is an advanced estimate of the retail sales value.

Also take a look at year over year

Retail sales and the labor market

Income

Real Personal Income

Real Personal Income (Excluding Transfer, Annual)

During a recession real personal income falls. In the plot the peaks can be seen prior to each recession.

datay <- "W875RX1"
ylim <- c(3000, 15000)
plotSingleQuickModern(datay, ylim)

The features we are interested in are the peaks and valleys so we’ll use the derivative to get to those. Interesting, there is usually a first zero crossing before a recession and a second during or just after the recession.

Real personal income might have some seasonal variance, but it seems the year over year change tells the same story.

Price and cost measures

This section shows price and cost measures.

Two commonly used indexes are the CPI (consumer price index) and PPI (producer price index). CPI tries to show final prices paid for goods and services by urban U.S. consumers. This index includes sales tax and imports. The PPI attempts to reflect the prices paid at all stages of production, including goods and services purchases as inputs as well as goods and services purchased by consumers from retail and producer sellers. The PPI does not include imports or sales tax. The CPI reflects all rebates and financing plans wherease the PPI reflects only those rebate and financing plans provided by the producer. For example if an automotive manufacturer offers a rebate of $500 and the dealer offers an additional rebate of $500 then the PPI would reflect only the automotive manufacturer rebate, but the CPI would reflect both rebates.

Sources; https://www.bls.gov/opub/hom/pdf/cpihom.pdf and https://www.bls.gov/opub/hom/pdf/ppi-20111028.pdf.

Consumer price index

What does CPI look like?

datay <- "CPIAUCSL"
ylim <- c(0, 300)
plotSingleQuickModern(datay, ylim)

Check out the YoY growth

datay <- "CPIAUCSL_YoY"
ylim <- c(-2, 15)
plotSingleQuickModern(datay, ylim)

CPI to PPI

Suggested by Charlie, it can be helpful to look at the relationship between producer prices and consumer prices.

## Scale for 'y' is already present. Adding another scale for 'y', which will
## replace the existing scale.

Producer Price Index (Commodities)

Commodities

Basket

Take a look at some trends of baskets of commodities.

This plot examines commodity performance relative to the GDP deflator

Crude oil

Look at a trend of West Texas Intermediate (WTI)

This is ticker data from yahoo

Take a look at both WTI and Brent crude.

Real price of crude using producer price index for commodities

Gold

As risks increase investors often flock to safe haven assets like gold. An up-tick in prices can indicate investor uncertainty. This can be seen in the nominal price plot around 1980 and again in 2007.

This plots out the real price of gold by two different deflators. PPI corrected price is a little higher, to be expected since CPI also includes the effects of sales tax and imports. The spike in 1980 is especially pronounced in this series.

See how nominal and real prices look year over year. From the long-term view seems like there is little difference in the three series. Although not shown, even over the near-term there is little difference in the series.

See how gold correlates with the VIX. Both gold and VIX should respond to investor axiety, but it doesn’t look like it correlates very well.

## `geom_smooth()` using formula 'y ~ x'
## Warning: Removed 242 rows containing non-finite values (stat_smooth).

Copper

Dr. Copper has a reputation as an indicator of economic malaise, but it does not seem to have much of a correlation with the recessions. The series below is from CME via Quandl. It has a lot of data so I am also looking at the smoothed version.

Copper is one of the commodities in the PPI so it is a bit of a proxy for how copper is doing relative to the basket of commodities.

The change in prices, year over year, do generally peak prior to a recession. The time and shape of this peak varies, but it still might be helpful. A couple of the large troughs do seem to correlate with the end of the recession. Likely this is because industrial production has also fallen.

There is some correlation between copper and the smooth recession initiator, especially at the end of the recession.

Might be easier to see correlation in a dot plot format.

## `geom_smooth()` using formula 'y ~ x'
## Warning: Removed 342 rows containing non-finite values (stat_smooth).

This is a legacy series from FRED. It has not been updated in a couple of years so I am assuming it will go away.

Oil Services

Amazing events in the first half of 2020, take a look at those

See how the players are doing

Federal Reserve

The federal reserve has an impact on the economy, here are some data series relating to that.

Little bit closer

datay <- "WALCL"
ylim <- c(0, 10000)
dtStart = as.Date('2003-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

Federal Reserve Reverse Repo Agreements

Compare liabilities to reverse repo trends

Take a look at more recent trends

Spiky, might be easier to look at year-over-year

Normalized by GDP

datay <- "WLRRAL.by.GDP"
ylim <- c(0, 4)
dtStart = as.Date('2003-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

Overnight Bank Funding Rate

“The overnight bank funding rate is calculated using federal funds transactions and certain Eurodollar transactions. The federal funds market consists of domestic unsecured borrowings in U.S. dollars by depository institutions from other depository institutions and certain other entities, primarily government-sponsored enterprises, while the Eurodollar market consists of unsecured U.S. dollar deposits held at banks or bank branches outside of the United States. U.S.-based banks can also take Eurodollar deposits domestically through international banking facilities (IBFs). The overnight bank funding rate (OBFR) is calculated as a volume-weighted median of overnight federal funds transactions and Eurodollar transactions reported in the FR 2420 Report of Selected Money Market Rates. Volume-weighted median is the rate associated with transactions at the 50th percentile of transaction volume. Specifically, the volume-weighted median rate is calculated by ordering the transactions from lowest to highest rate, taking the cumulative sum of volumes of these transactions, and identifying the rate associated with the trades at the 50th percentile of dollar volume. The published rates are the volume-weighted median transacted rate, rounded to the nearest basis point.” https://www.newyorkfed.org/markets/obfrinfo.

Secured Overnight Financing Rate

“The Secured Overnight Financing Rate (SOFR) is a broad measure of the cost of borrowing cash overnight collateralized by Treasury securities. The SOFR includes all trades in the Broad General Collateral Rate plus bilateral Treasury repurchase agreement (repo) transactions cleared through the Delivery-versus-Payment (DVP) service offered by the Fixed Income Clearing Corporation (FICC), which is filtered to remove a portion of transactions considered “specials” " https://apps.newyorkfed.org/markets/autorates/sofr

Take a look at the variation (99th - 1st percentile)

Reserve Balances with Federal Reserve Banks

Hard to get a sense of these series in the absolute. Take a look relative to GDP.

By double entry book-keeping reserves+loans (assets) = deposit (liabilities). Does that really work?

Correlation Between Reserves and Total Loans

As reserves increase there should be less lending. That correlation generally holds.

## Scale for 'y' is already present. Adding another scale for 'y', which will
## replace the existing scale.

Did the reserve balances increase after the 2016 and 2018 drops? Not in the same way. There are some relationships between the equities market and the reserves though.

Explicitly correlate reserve balances and total loans. It is a weak and noisy correlation.

## `geom_smooth()` using formula 'y ~ x'
## Warning: Removed 990 rows containing non-finite values (stat_smooth).

Interest on excess reserves

Monetary Base

Currency trend, base

This used to trend along with GDP. It doesn’t anymore.

Money supplies

Basic currency trend (currency component of M1)

datay <- "WCURRNS_YoY"
dtStart = as.Date('1980-01-01')
ylim <- c(0, 17)
myplot <- plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)
myplot

datay <- "WCURRNS_YoY"
dtStart = as.Date('2000-01-01')
ylim <- c(0, 20)
myplot <- plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)
myplot

The rate of change of money supply could be an indicator of a recession. Let’s see how that compares.

Intervention in the repo market

The federal reserve provides liquidity to the repo market, summary of that action

European central bank

The European central band (ECB) has taken a different path compared to the US Federal Reserve bank.

## Scale for 'y' is already present. Adding another scale for 'y', which will
## replace the existing scale.

Federal Debt

The government is a big driver of the economy, let’s see what it is doing in the debt markets.

datay <- "GFDEBTN"
ylim <- c(0, 35000000)
plotSingleQuick(dfRecession, df.data, datay, ylim)

datay <- "GFDEBTN_Log"
ylim <- c(12, 18)
plotSingleQuick(dfRecession, df.data, datay, ylim)

datay <- "GFDEBTN_YoY"
ylim <- c(-10, 25)
plotSingleQuick(dfRecession, df.data, datay, ylim)

Federal debt as percent GDP

datay <- "GFDEGDQ188S"
ylim <- c(30, 150)
plotSingleQuick(dfRecession, df.data, datay, ylim)

Federal deficit as percent GDP

datay <- "FYFSGDA188S"
ylim <- c(-30, 5)
plotSingleQuick(dfRecession, df.data, datay, ylim)

Charlie Hatch has a nice format of deficit versus debt:

## Scale for 'y' is already present. Adding another scale for 'y', which will
## replace the existing scale.

Nonfinancial Corporate Business Debt

What about Nonfinancial corporate business and debt securities? Hopefully this doesn’t follow the business loan trends.

That is crazy steep. Time for a log format, see if that brings out the peaks and troughs. That’s a litte better, it looks like there might be a change in slope prior to the recessions.

The derivative doesn’t seem to be much help. There is not much correlation between the zero crossings and the NEBR recessions.

Debt cycle

This analysis roughly follows the ideas in Big Debt Crises book by Ray Dalio.

Total loans

One business cycle theory describes recessions as a market adjustment to mis-allocated assets, often fueled by an credit expansion. That makes the volume of loans an interesting feature to look at. In the presentation of data it looks like the great recession had the largest impact.

Plotting the year over year growth rate helps pull out those small changes in the early years in the data. Peaks can be seen prior to most recessions.

Zoom in to the last couple of decades

As long term interest rates rise, loans should start to tick down. To check this, the total loans and 10 to 1 year spreads are plotted. This is generally the trend observed.

There is a good correlation between these two variables. This next section plots that correction explicitly.

Total loans as percent of GDP

This is the total loans. I think the picture is too broad to point to a specific sector of the economy. The debt burden assumes interest rates are tied to the 10-year treasury: (TOTLNNSA * DGS10) / 100

Commercial and industral loans

Business loans should slow before the recession (a contraction in credit as rates rise).

Commercial and industrial loans as percent of GDP and and income

Look at business debt normalized by GDP over the entire time series. This ratio often peaks at the mid-point of a recession.

https://www.wsj.com/articles/this-isnt-your-fathers-corporate-bond-market-11590574555

“Bonds are behaving more like bank debt, which tends to remain stable or even increase at the onset of recessions, as lenders keep distressed clients afloat—and only later turn off the taps. This was confirmed by a recent report from the Bank for International Settlements. It also found a tight link between this lending cycle and the “real” economy’s booms and busts."

I assume that interest is related to the 10-year treasure: (TOTCINSA * DGS10) / 100

Farm loans

See how the farming sector is fairing.

Real estate loans

Data taken from H.8 Assets and Liabilities of Commercial Banks in the United States. Take a look at SA and NSA data series as weekly and month updates. It should all be similar at this scale.

This gives a big picture, but makes it hard to connect the loans with the income needed to cover those loans. In the next section, loans will be broken up by commercial and residential.

Real Estate (Residential)

In absolute terms the mortgages have increased, but it does not appear to be out of line with the overall economy.

Normalized by GDP it is easier to see the peak in 2008 and that loan levels appear reasonable at the commercial banks. I updated this plot to include the estimated single-family home sales volume to give a sense of percentage of home sales that are cash.

Maybe the GSE’s are making loans. Take a look at the total mortgages from Z.1 as a percentage of GDP. That does not look too far off trend (ignoring that peak in 2008).

I am assuming that personal income is paying for the mortgages.

Real estate (residential) as percent of GDP and and income

## Warning: Removed 1 rows containing missing values (geom_text).

How do the number of starts compare to population?

Consumer loans

Focusing on the consumer sector the growth in debt and incomes can be directly compared. Personal income, as a percent of GDP, remains nearly constant. It is not uncommon for the personal income to rise prior to a recession. Likely this reflect increasing asset prices and market returns. Also interesting to see the loans pick up after interest rates dropped in 1982.

Consumer loans as percent of GDP and and income

Take a closer look since the 2008 recession. Looks like loans are starting to slow as the interest burden rises and incomes remain stable. There are some anomolies in the A065RC1A027NBEA data series because it only updates onces a year. the PI series updates once a month but is noisier and seasonally adjusted. It also shows incomes rising in the middle of the 2008 recession, which doesn’t seem to be accurate.

## Warning: Removed 1 rows containing missing values (geom_text).
## Removed 1 rows containing missing values (geom_text).
## Warning: Removed 1 rows containing missing values (geom_hline).

Repo market

This market went through some stress in 2008, it is happening again so setup some plots to watch it.

Nonfincial corporate business security repo asset level

Bonds

T-Bills and Yield Curve

Speaking of loans, interest rates also play into this. This analysis will focus on treasure bills. The 3-month is plotted below. The yield flattens before a recession as investors go long on bonds and short on equities.

datay <- "TB3MS"
datay.aux <- "DTB3"
ylim <- c(0, 20)
p1 <- plotSingleQuickModern(datay, ylim)
p1 + geom_line(data=df.data, aes_string(x="date", y=datay.aux, colour=shQuote(datay.aux)), na.rm = TRUE)

datay <- "TB3MS"
datay.aux <- "DTB3"
ylim <- c(0, 6.0)
dtStart = as.Date('2017-01-01')
p1 <- plotSingle(dfRecession, df.data, "date", datay, getPlotTitle(df.symbols, datay), "Date", 
            getPlotYLabel(df.symbols, datay), c(dtStart, Sys.Date()), ylim, TRUE)
p1 + geom_line(data=df.data, aes_string(x="date", y=datay.aux, colour=shQuote(datay.aux)), na.rm = TRUE)

# {r bond3monthlibor, echo=FALSE } # # datay <- "TB3MS" # datay_aux <- "USD1MTD156N" # ylim <- c(0, 12) # dtStart = as.Date('1985-01-01') # myPlot <- plotSingle(dfRecession, df.data, "date", datay, getPlotTitle(df.symbols, datay), "Date", # getPlotYLabel(df.symbols, datay), c(dtStart, Sys.Date()), ylim, TRUE) # myPlot <- myPlot + geom_line(data=df.data, aes_string(x="date", y=datay_aux, colour=shQuote(datay_aux)), na.rm = TRUE) # # myPlot # # Check out LIBOR and fed funds rate

The 1-year is plotted below. The yield flattens before a recession as investors go long on bonds and short on equities.

datay <- "DGS10"
datay.aux <- "TNX.Close"
ylim <- c(0, 20)
p1 <- plotSingleQuickModern(datay, ylim)
p1 + geom_line(data=df.data, aes_string(x="date", y=datay.aux, colour=shQuote(datay.aux)), na.rm = TRUE)

Close in, the trend towards inversion be more easily seen. I am also comparing data from the CBOE as well as FRED.

Bond yields are a good proxy for interest rates. As rates rise the theory goes that loans should decrease (inverse correlation).

And a longer window

The yield curve (30 year bond rate minus the 10 year bond rate) may not be a good recession indicator, but a collapse is not good (https://blogs.wsj.com/moneybeat/2018/04/30/theres-more-than-one-part-of-the-yield-curve-getting-flatter/).

The yield curve (10 year bond rate minus the 1 year bond rate) seems to a good indicator of an oncoming recession. It could be a buy indicator by itself.

More recent data

Just the last 24 months or so.

Plot the 10 Year to 3 month over a few decades to see what the outling cases look like

The last two year compare favorably with the period around the 2015-2016 turndown, driven primarily by slowing of the Chinese GDP. Not a debt-driven cycle.

This plot format was suggested by a mises.org article (https://mises.org/wire/yield-curve-accordion-theory), but they only went back to 1988. The date seemed arbitrary so I went back further in time.

Take a look at more recent data

Try looking at a 1-year average of the above time series

High quality bonds

datay <- "AAA"
ylim <- c(1.5, 10)
dtStart = as.Date('1997-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

High quality bonds to 10-year treasury

High quality bonds long-term trend.

datay <- "DGS10ByAAA"
ylim <- c(1, 6.0)
dtStart = as.Date('1967-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

High quality bonds near-term trend.

datay <- "DGS10ByAAA"
ylim <- c(1, 6.0)
dtStart = as.Date('2007-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

High yield spread

“This data represents the Option-Adjusted Spread (OAS) of the ICE BofAML US Corporate A Index, a subset of the ICE BofAML US Corporate Master Index tracking the performance of US dollar denominated investment grade rated corporate debt publicly issued in the US domestic market. This subset includes all securities with a given investment grade rating A. The ICE BofAML OASs are the calculated spreads between a computed OAS index of all bonds in a given rating category and a spot Treasury curve. An OAS index is constructed using each constituent bond‚Äôs OAS, weighted by market capitalization. When the last calendar day of the month takes place on the weekend, weekend observations will occur as a result of month ending accrued interest adjustments.”

  • ICE Benchmark Administration Limited (IBA), ICE BofAML US Corporate A Option-Adjusted Spread [BAMLC0A3CA], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/BAMLC0A3CA, July 4, 2019.
datay <- "BAMLC0A3CA"
ylim <- c(0, 7)
dtStart = as.Date('1997-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

Municipal bond market

Suggest by a WSJ article, change in volume for high-risk muni’s. Doesn’t look like there is much too it yet.

https://www.wsj.com/articles/risky-municipal-bonds-are-on-a-hot-streak-11558949401?mod=hp_lead_pos3

datay <- "HYMB.Close"
ylim <- c(40, 62)
dtStart = as.Date('2011-01-01')
p1 <- plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

p1 <-
  p1 + geom_vline(
    xintercept = as.Date("2015-08-24"),
    linetype = "dashed",
    color = "grey",
    size = 1.0
  )

p1 <-
  p1 + geom_vline(
    xintercept = as.Date("2016-01-08"),
    linetype = "dashed",
    color = "grey",
    size = 1.0
  )
p1 <-
  p1 + geom_vline(
    xintercept = as.Date("2018-02-05"),
    linetype = "dashed",
    color = "grey",
    size = 1.0
  )
p1 <-
  p1 + geom_vline(
    xintercept = as.Date("2018-10-11"),
    linetype = "dashed",
    color = "grey",
    size = 1.0
  )

datay <- "HYMB.Volume"
ylim <- c(0, 1750000)
p1.vol <- plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

p1.vol <-
  p1.vol + geom_vline(
    xintercept = as.Date("2015-08-24"),
    linetype = "dashed",
    color = "grey",
    size = 1.0
  )

p1.vol <-
  p1.vol + geom_vline(
    xintercept = as.Date("2016-01-08"),
    linetype = "dashed",
    color = "grey",
    size = 1.0
  )
p1.vol <-
  p1.vol + geom_vline(
    xintercept = as.Date("2018-02-05"),
    linetype = "dashed",
    color = "grey",
    size = 1.0
  )
p1.vol <-
  p1.vol + geom_vline(
    xintercept = as.Date("2018-10-11"),
    linetype = "dashed",
    color = "grey",
    size = 1.0
  )


datay <- "GSPC.Open"
datay_aux <- "GSPC.Close"
ylim <- c(1500, d.GSPC.max )
p2 <-
  plotSingle(
    dfRecession,
    df.data,
    "date",
    datay,
    getPlotTitle(df.symbols, datay),
    "Date",
    getPlotYLabel(df.symbols, datay),
    c(dtStart, Sys.Date()),
    ylim,
    TRUE
  )

p2 <-
  p2 + geom_vline(
    xintercept = as.Date("2015-08-24"),
    linetype = "dashed",
    color = "grey",
    size = 1.0
  )
p2 <-
  p2 + geom_vline(
    xintercept = as.Date("2016-01-08"),
    linetype = "dashed",
    color = "grey",
    size = 1.0
  )
p2 <-
  p2 + geom_vline(
    xintercept = as.Date("2018-02-05"),
    linetype = "dashed",
    color = "grey",
    size = 1.0
  )
p2 <-
  p2 + geom_vline(
    xintercept = as.Date("2018-10-11"),
    linetype = "dashed",
    color = "grey",
    size = 1.0
  )


grid.arrange(p1,
             p1.vol,
             p2,
             ncol = 1,
             top = "High Yield Muni's and S&P Price")

Total Loans and yield curve correlation

This relationship was suggest by Charlie and it is an interesting one. As the yield curve flattens (10-year and 1-year rates converge), total loans grow. The generalization is not always accurate, but it does fit.

## `geom_smooth()` using formula 'y ~ x'

I wanted to see how this looked compared to the 3 month

## `geom_smooth()` using formula 'y ~ x'
## Warning: Removed 282 rows containing non-finite values (stat_smooth).

Consumer loans and yield curve correlation

Compared to business loans, consumer loans seem to have to response to the 10Y to 3M yield curve.

## `geom_smooth()` using formula 'y ~ x'
## Warning: Removed 311 rows containing non-finite values (stat_smooth).

Business loans and yield curve correlation

## `geom_smooth()` using formula 'y ~ x'
## Warning: Removed 104 rows containing non-finite values (stat_smooth).

That’s pretty good correlation. Let’s see what the rolling correlation looks like.

datay1 <- "TOTLNNSA_YoY"
ylim1 <- c(-10, 20)

datay2 <- "DGS10TO1"
ylim2 <- c(-5, 10)

dtStart <- as.Date("1jan1960","%d%b%Y")

w <- 360
corrName <- calcRollingCorr(dfRecession, df.data, df.symbols, datay1, ylim1, datay2, ylim2, w, dtStart)

datay1 <- "TOTLNNSA_YoY"
ylim1 <- c(-10, 20)

datay2 <- "DGS10TO1"
ylim2 <- c(-5, 10)

dtStart <- as.Date("1jan1960","%d%b%Y")

w <- 720
corrName <- calcRollingCorr(dfRecession, df.data, df.symbols, datay1, ylim1, datay2, ylim2, w, dtStart)

One other items, let’s see how loans do versus the federal funds rate

## `geom_smooth()` using formula 'y ~ x'

Baker Hughes Rig Count

BEA Supplemental Estimates, Motor Vehicles

Definitions

Autos–all passenger cars, including station wagons.
Light trucks–trucks up to 14,000 pounds gross vehicle weight, including minivans and
sport utility vehicles. Prior to the 2003 Benchmark Revision light trucks were up to 10,000 pounds.
Heavy trucks–trucks more than 14,000 pounds gross vehicle weight.
Prior to the 2003 Benchmark Revision heavy trucks were more than 10,000 pounds.
Domestic sales–United States (U.S.) sales of vehicles assembled in the U.S., Canada, and Mexico.
Foreign sales–U.S. sales of vehicles produced elsewhere.
Domestic auto production–Autos assembled in the U.S.
Domestic auto inventories–U.S. inventories of vehicles assembled in the U.S., Canada, and Mexico.

TAble 6 - Light Vehicle and Total Vehicle Sales

Auto sales

A WSJ article suggested that auto sales might be a good indicator so bring that to the mix. It does have troughs that correlate with recessions

There might be some seasonal variance in the auto sales so lets take a look at the year over year. The data is pretty noisy, it probably will not make a very good indicator.

BEA Gross Domestic Product

Data in this section come from the Bureau of Economic Analysis.

Table 1.1.5. Gross Domestic Product

[Billions of dollars] Seasonally adjusted at annual rates

A191RC: Gross Domestic Product - Line 1

GDP numbers tend to lag so this series is truly an afterthought. But it does have some correlation with the recessions.

GDP does not reflect the capacity of the economy nor the efficiency. Shrinking capacity and lower prices at constant volumes would indicate improvements in effeciency/productivity which is good for the economy, but does not move the GDP upward.

Looks like the year over year change on the GDP should correlate well with unemployment.

Table 1.1.9. Implicit Price Deflators for Gross Domestic Product

[Index numbers, 2012=100] Seasonally adjusted

A191RD: Gross Domestic Product - Line 1

This is GDP price deflator series.

GDP normalized by CPI

Normalize GDP by CPI

Economic yield curve (GDP to 1-year treasury)

GDP versus the yield on the 1-year. This series was prompted by an article suggesting that the “economic yield curve” should be used to indicate a recession rather than an inverted yield curve. Less of indicator and more of concurrent confirmation of recession. Not sure why they would be related either.

Economic yield curve (GDP to 3-month treasury)

Same idea as above, but applied the 3-month treasury.This one has fewer false triggers, but is not as helpful as 10Y to 3M spread in predicting a recession.

A824RC: National defense Federal Gov’t Expenditures - Line 24

U.S. Bureau of Economic Analysis, Federal Government: National Defense Consumption Expenditures and Gross Investment [FDEFX], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/FDEFX, April 6, 2021.

A825RC: Nondefense Federal Gov’t Expenditures - Line 25

U.S. Bureau of Economic Analysis, Federal Government: Nondefense Consumption Expenditures and Gross Investment [FNDEFX], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/FNDEFX, April 6, 2021.

Table 6.16D. Corporate Profits by Industry

Select series from Table 6.16D

A051RC: Corporate profits with inventory and capital consumption adjustment

From BEA’s documentation (https://www.bea.gov/media/5671):

“BEA’s featured measure of corporate profits — profits from current production - provides a comprehensive and consistent economic measure of the income earned by all U.S. corporations. As such, it is unaffected by changes in tax laws, and it is adjusted for nonreported and misreported income. It excludes dividend income, capital gains and losses, and other financial flows and adjustments, such as deduction for “bad debt.” Thus, the NIPA measure of profits is a particularly useful analytical measure of the health of the corporate sector. For example, in contrast to other popular measures of corporate profits, the NIPA measure did not show the large run-up in profits during the late 1990s that was primarily attributable to capital gains.

Profits after tax with IVA and CCAdj is equal to corporate profits with IVA and CCAdj less taxes on corporate income. It provides an after-tax measure of profits from current production."

Data is Line 1 of Table 6.16D

A053RC: Corporate profits without inventory and capital consumption adjustment

Profits look a bit flat over the last several years in this series.

Table 2.6. Personal Income and Its Disposition, Monthly

Billions of dollars; months are seasonally adjusted at annual rates.

A065RC Personal Income - Line 1

BEA Account Code: A065RC

Personal income is the income that persons receive in return for their provision of labor, land, and capital used in current production and the net current transfer payments that they receive from business and from government.25 Personal income is equal to national income minus corporate profits with inventory valuation and capital consumption adjustments, taxes on production and imports less subsidies, contributions for government social insurance, net interest and miscellaneous payments on assets, business current transfer payments (net), current surplus of government enterprises, and wage accruals less disbursements, plus personal income receipts on assets and personal current transfer receipts. A Guide to the National Income and Product Accounts of the United States (NIPA) - (http://www.bea.gov/national/pdf/nipaguid.pdf)

Suggested Citation: U.S. Bureau of Economic Analysis, Personal Income [PI], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/PI, July 11, 2019.

DPCERC: Personal consumption expenditures (PCE) - Table 2.1, Line 29

BEA Account Code: DPCERC Personal consumption expenditures (PCE) is the primary measure of consumer spending on goods and services in the U.S. economy. 1 It accounts for about two-thirds of domestic final spending, and thus it is the primary engine that drives future economic growth. PCE shows how much of the income earned by households is being spent on current consumption as opposed to how much is being saved for future consumption. -https://www.bea.gov/system/files/2019-12/Chapter-5.pdf

Suggested Citation: U.S. Bureau of Economic Analysis, Personal Consumption Expenditures [PCE], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/PCE, June 12, 2020

DPCERG: Personal consumption expenditures Price Index (PCEPI) - Table 2.1, Line 29

BEA Account Code: DPCERG The gross domestic product price index measures changes in prices paid for goods and services produced in the United States, including those exported to other countries. Prices of imports are excluded. The gross domestic product implicit price deflator, or GDP deflator, basically measures the same things and closely mirrors the GDP price index, although the two price measures are calculated differently. The GDP deflator is used by some firms to adjust payments in contracts.

The gross domestic purchases price index is BEA’s featured measure of inflation for the U.S. economy overall. It measures changes in prices paid by consumers, businesses, and governments in the United States, including the prices of the imports they buy.

BEA’s closely followed personal consumption expenditures price index, or PCE price index, is a narrower measure. It looks at the changing prices of goods and services purchased by consumers in the United States. It’s similar to the Bureau of Labor Statistics’ consumer price index for urban consumers. The two indexes, which have their own purposes and uses, are constructed differently, resulting in different inflation rates.

The PCE price index is known for capturing inflation (or deflation) across a wide range of consumer expenses and for reflecting changes in consumer behavior. For example, if the price of beef rises, shoppers may buy less beef and more chicken. Also, BEA revises previously published PCE data to reflect updated information or new methodology, providing consistency across decades of data that’s valuable for researchers. The PCE price index is used primarily for macroeconomic analysis and forecasting. -https://www.bea.gov/resources/learning-center/what-to-know-prices-inflation

Suggested Citation: U.S. Bureau of Economic Analysis, Personal Consumption Expenditures: Chain-type Price Index [PCEPI], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/PCEPI, April 25, 2021.

A072RC: Personal Savings Rate - Line 35

Consumers tend to pull down their savings rates as unemployment decreases and market conditions improve. This series has tended to be unreliable due to the size of revisions during the comprehensive update carried out by the BEA. The last update on this series moved the rate from 4.2 to 6.7 percent.

(https://www.bloomberg.com/news/articles/2018-07-27/americans-have-been-saving-much-more-than-thought-new-data-show)

BEA Account Code: A072RC Personal saving as a percentage of disposable personal income (DPI), frequently referred to as “the personal saving rate,” is calculated as the ratio of personal saving to DPI. Personal saving is equal to personal income less personal outlays and personal taxes; it may generally be viewed as the portion of personal income that is used either to provide funds to capital markets or to invest in real assets such as residences.(https://www.bea.gov/national/pdf/all-chapters.pdf) A Guide to the National Income and Product Accounts of the United States (NIPA).

Suggested Citation: U.S. Bureau of Economic Analysis, Personal Saving Rate [PSAVERT], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/PSAVERT, July 9, 2019.

Take a closer look at the last decade

The relationship between personal savings and unemployment (U-3) can be better visualized with a scatter plot

## `geom_smooth()` using formula 'y ~ x'
## Warning: Removed 172 rows containing non-finite values (stat_smooth).

The fit does not explain most of what is in the plot. Lets take a look at the rolling correlation.

datay1 <- "UNRATE"
ylim1 <- c(2, 12)

datay2 <- "PSAVERT"
ylim2 <- c(0, 35)

dtStart <- as.Date("1jan1985","%d%b%Y")

w <- 360
corrName <- calcRollingCorr(dfRecession, df.data, df.symbols, datay1, ylim1, datay2, ylim2, w, dtStart)

Personal savings to household net worth

A relationship between personal savings and household networth can be seen in a scatter plot. This was suggested by a WSJ article (https://blogs.wsj.com/dailyshot/2018/02/23/the-daily-shot-reasons-for-declining-u-s-household-savings-rate/).

## `geom_smooth()` using formula 'y ~ x'
## Warning: Removed 1158 rows containing non-finite values (stat_smooth).

U.S. Census Bureau

U.S. International Trade in Goods and Services (FT900)

U.S. Bureau of Economic Analysis and U.S. Census Bureau, U.S. Imports of Goods by Customs Basis from China [IMPCH], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/IMPCH, October 5, 2019.

New Houses Sold and For Sale by Stage of Construction and Median Number of Months on Sales Market

Read an article suggesting that housing sales and sales growth could be useful. FRED only has new home data so start there.

datay <- "HSN1FNSA"
ylim <- c(0, 200)
dtStart = as.Date('1964-01-01')
p1 <- plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

datay <- "HNFSUSNSA"
ylim <- c(0, 600)
p2 <- plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

datay <- "HNFSUSNSA.minus.HSN1FNSA"
ylim <- c(0, 600)
p3 <-
  plotSingle(
    dfRecession,
    df.data,
    "date",
    datay,
    getPlotTitle(df.symbols, datay),
    "Date",
    getPlotYLabel(df.symbols, datay),
    c(dtStart, Sys.Date()),
    ylim,
    TRUE
  )

grid.arrange(p1,
             p2,
             p3,
             ncol = 1,
             top = "New Housing Sales")

New housing yoy

New Privately-Owned Housing Units Authorized in Permit-Issuing Places

As provided by the Census, start occurs when excavation begins for the footings or foundation of a building. All housing units in a multifamily building are defined as being started when this excavation begins. Beginning with data for September 1992, estimates of housing starts include units in structures being totally rebuilt on an existing foundation.

Suggested Citation: U.S. Census Bureau and U.S. Department of Housing and Urban Development, Housing Starts: Total: New Privately Owned Housing Units Started [HOUST], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/HOUST, June 13, 2020.

Take a look at privately owned starts

New Privately-Owned Houses Sold and For Sale

Suggested Citation: U.S. Census Bureau and U.S. Department of Housing and Urban Development, Median Sales Price of Houses Sold for the United States [MSPUS], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/MSPUS, June 13, 2020.

Finally, take a look at starts times the median price

Durable Goods

Suggested Citation: U.S. Census Bureau, Manufacturers’ New Orders: Durable Goods [UMDMNO], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/UMDMNO, April 26, 2021.

Durable goods, not seasonally adjusted, divided by GDP

Durable goods, seasonally adjusted, divided by GDP

Federal reserve board H.8: Assets and Liabilities of Commercial Banks in the United States

Page 4: Not Seasonally adjusted, billions of dollars

Commercial and industrial loans, all commercial banks - Line 10

Data taken from H.8 Assets and Liabilities of Commercial Banks in the United States. Take a look at SA and NSA data series as weekly and month updates. It should all be similar at this scale.

Suggested Citation: Board of Governors of the Federal Reserve System (US), Commercial and Industrial Loans, All Commercial Banks [BUSLOANS], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/BUSLOANS, July 11, 2019.

Taking a look at the difference in SA and NSA series. Seasonal adjustments do vary, but do not seem to be related to recessions.

The raw series is just too steep for any kind of machine learnine. This needs to be converted to log scale.

That’s a little better, let’s see what the smoothed derivative looks like.

That is odd…looks like this doesn’t cross zero unless we are getting close to, or into, a recession. The year over year tells about the same story. Might be a good indication of the end of a recession.

Consumer loans, all commercial banks - Line 20

Suggested Citation: Board of Governors of the Federal Reserve System (US), Consumer Loans, All Commercial Banks [CONSUMERNSA], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/CONSUMERNSA, July 11, 2019.

That spike in consumer loans is due to

“April 9, 2010 (Last revised September 23, 2011): As of the week ending March 31, 2010, domestically chartered banks and foreign-related institutions had consolidated onto their balance sheets the following assets and liabilities of off-balance-sheet vehicles, owing to the adoption of FASB’s Financial Accounting Statements No. 166 (FAS 166),”Accounting for Transfers of Financial Assets," and No. 167 (FAS 167), “Amendments to FASB Interpretation No. 46(R).”

This included a consumer loans, credit cards and other revolving plans change of $321.9B. That was a lot of off-balance-sheet bank assets.

Deposits, All Commercial Banks, all commercial banks - Line 34

Data taken from H.8 Assets and Liabilities of Commercial Banks in the United States. Take a look at SA and NSA data series as weekly and month updates. It should all be similar at this scale.

Suggested Citation: Board of Governors of the Federal Reserve System (US), Deposits, All Commercial Banks [DPSACBW027SBOG], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/DPSACBW027SBOG, May 14, 2020.

Federal reserve board Z.1: Financial Accounts of the United States

From the FRED website (https://fred.stlouisfed.org/release?rid=52):

"The Financial Accounts (formerly known as the Flow of Funds accounts) are a set of financial accounts used to track the sources and uses of funds by sector. They are a component of a system of macroeconomic accounts including the National Income and Product accounts (NIPA) and balance of payments accounts, all of which serve as a comprehensive set of information on the economy’s performance.(1) Some important inferences that can be drawn from the Financial accounts are the financial strength of a given sector, new economic trends, changes in the composition of wealth, and development of new financial instruments over time.(1)

Sectors are compiled into three categories: households, nonfinancial businesses, and banks. The sources of funds for a sector are its internal funds (savings from income after consumption) and external funds (loans from banks and other financial intermediaries). (1) Funds for a given sector are used for its investments in physical and financial assets. Dividing sources and uses of funds into two categories helps the staff of the Federal Reserve System pay particular attention to external sources of funds and financial uses of funds.(2) One example is whether households are borrowing more from banks—or in other words, whether household debt is rising. Another example might be whether banks are using more of their funds to provide loans to consumers. Transactions within a sector are not shown in the accounts; however, transactions between sectors are.(2) Monitoring the external flows of funds provides insights into a sector’s health and the performance of the economy as a whole.

Data for the Financial accounts are compiled from a large number of reports and publications, including regulatory reports such as those submitted by banks, tax filings, and surveys conducted by the Federal Reserve System.(2) The Financial accounts are published quarterly as a set of tables in the Federal Reserve’s Z.1 statistical release.

  1. Teplin, Albert M. “The U.S. Flow of Funds Accounts and Their Uses.” Federal Reserve Bulletin, July 2001; http://www.federalreserve.gov/pubs/bulletin/2001/0701lead.pdf.
  2. Board of Governors of the Federal Reserve System. “Guide to the Flow of Funds Accounts.” 2000, http://www.federalreserve.gov/apps/fof/."

L.102 Nonfinancial Business

FL102051003.Q: Nonfinancial corporate business; security repurchase agreements; asset

Asset level of nonfinancial business security repo agreements. federalreserve.gov/apps/fof/SeriesAnalyzer.aspx?s=FL102051003&t=

L.214 Loans

FL894123005.Q: All sectors; total loans; liability

Sum of domestic financial sectors, all sectors, total mortgages, and households/non-profits. federalreserve.gov/apps/fof/SeriesAnalyzer.aspx?s=FL894123005&t=L.107&bc=L.107:FL793068005&suf=Q

FL793068005.Q: Domestic financial sectors; depository institution loans n.e.c.; asset

Sum of Monetary authority; depository institution loans n.e.c.; asset and Private depository institutions; depository institution loans n.e.c.; asset. federalreserve.gov/apps/fof/SeriesAnalyzer.aspx?s=FL793068005&t=L.214&suf=Q

FL893169005.Q: All sectors; other loans and advances; liability

Sum of finance, government, and chartered institutions asset levels. https://www.federalreserve.gov/apps/fof/SeriesAnalyzer.aspx?s=FL893169005&t=L.214&suf=Q

FL893065105.Q: All sectors; home mortgages; asset

https://www.federalreserve.gov/apps/fof/DisplayTable.aspx?t=L.214

FL893065405.Q: All sectors; multifamily residential mortgages; asset

https://www.federalreserve.gov/apps/fof/SeriesAnalyzer.aspx?s=FL893065405&t=L.214&suf=Q

FL893065505.Q: All sectors; commercial mortgages; asset

https://www.federalreserve.gov/apps/fof/SeriesAnalyzer.aspx?s=FL893065505&t=L.214&suf=Q

FL153166000.Q: Households and nonprofit organizations; consumer credit; liability

federalreserve.gov/apps/fof/SeriesAnalyzer.aspx?s=FL153166000&t=L.214&suf=Q

B.101 Balance Sheet of Households and Nonprofit Organizations

FL152000005.Q: Households and nonprofit organizations; total assets, Level

string.source ID: FL152000005.Q.

FL152090006.Q: Household Net Worth as Percentage of Disposable Personal Income

string.source ID: FL152090006.Q. Household networth tends to fall as a recession start.

Productivity Yield Curve

GDP versus productivity

Manufacturing output and employees

Not sure if these relates to a recession, but fascinating to see how output and employees change with time.

datay <- "OUTMS"
ylim <- c(60, 120)
dtStart = as.Date('1987-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

datay <- "MANEMP"
ylim <- c(10000, 20000)
dtStart = as.Date('1948-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

datay <- "PRS30006163"
ylim <- c(40, 120)
dtStart = as.Date('1986-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

Shipping volumes might be helpful in determining state of the economy.

datay <- "FRGSHPUSM649NCIS"
ylim <- c(0.8, 1.4)
dtStart = as.Date('1999-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

datay <- "FRGSHPUSM649NCIS_YoY"
ylim <- c(-30, 30)
dtStart = as.Date('1999-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

Freight, loosely, moves inversely to the trade deficit.

datay <- "BOPGTB_YoY"
ylim <- c(-30, 30)
dtStart = as.Date('1999-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

World bank air transportation. Only updated annually so less usefull, but interesting reference to above.

datay <- "WWDIWLDISAIRGOODMTK1"
ylim <- c(0, 250000)
dtStart = as.Date('1999-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

Gross private domestic investment

Spending most certainly tips down prior to a recession. The gross private domestic investment data series, plotted in log format below, show how private investment pulls back prior to recessions.

The change in direction is a little easier to see if the derivative is plotted, first YoY then the smoothed derivative

Velocity

Productivity

Frequency: Quarterly The Productivity and Costs release on August 7, 2003, will reflect the June 2003 benchmark revision to payroll employment. Since employment is now reported on a North American Industry Classification System (NAICS) basis, all of the historical data will be revised. Changes as a consequence of the move to NAICS should not be significant since this release carries data at high levels of aggregation.

Suggested Citation: U.S. Bureau of Labor Statistics, Nonfarm Business Sector: Labor Productivity (Output per Hour) for All Employed Persons [OPHNFB], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/OPHNFB, December 24, 2022.

Date range to match census data

PMI

Industrial Production

This is a look at manufacturing industrial production. The yoY change should be a leading indicator of unemployment.

Housing

Take a look at housing starts. These can drop as rates rise.

Frequency: Monthly

As provided by the Census, start occurs when excavation begins for the footings or foundation of a building. All housing units in a multifamily building are defined as being started when this excavation begins. Beginning with data for September 1992, estimates of housing starts include units in structures being totally rebuilt on an existing foundation.

Suggested Citation: U.S. Census Bureau and U.S. Department of Housing and Urban Development, New Privately-Owned Housing Units Started: Total Units [HOUST], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/HOUST, December 24, 2022.

Housing starts, NSA

HOUST reports at annual rate, but HOUSTNSA just reports the monthly numbers. I scale up the NSA to the annual rate.

Units: Thousands of Units, Not Seasonally Adjusted

Frequency: Monthly

Suggested Citation: U.S. Census Bureau and U.S. Department of Housing and Urban Development, New Privately-Owned Housing Units Started: Total Units [HOUSTNSA], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/HOUSTNSA, December 24, 2022.

Case-schiller price index

Population data

Many of the economic series can be better understood if normalized by population. Basic population and worker data from FRED.

Population to GDP

Look at GDP divided by CPI per person. It flattens and even dips a little prior to a recession. Might be worth looking at the derivative of this series.

That is worth a closer look

datay1 <- "GDPBYCPIAUCSLBYPOPTHM_SmoothDer"
ylim1 <- c(-5, 5)

datay2 <- "RecInit_Smooth"
ylim2 <- c(0, 1)

dtStart <- as.Date("1jan1960","%d%b%Y")

w <- 30
corrName <- calcRollingCorr(dfRecession, df.data, df.symbols, datay1, ylim1, datay2, ylim2, w, dtStart)

Correlation Study

Detailed correlations are explored above. Before concluding, let’s take a look at some overall correlation values to see if anything pops out.

Commodities

As mentioned above, copper, year over year, has some correlation with the recession initiation. It could be useful.

GDP Series

GDP, normalized first by CPI and then by population, looks like it migh correlate inversely with the recession indicators

Financials

Let’s see where we are so far. The correlation plot confirms some of the speculation above. The S&P 500 (GSPC.Open) is well correlated with industrial production (INDPRO), business loans (BUSLOANS), total loans (TOTLNNSA) , and nonfinancial corporate business debt (NCBDBIQ027S).

In this case, I want and indicator that rises prior to a recession. It looks like the unemployment rate (UNRATE), real personal income (W875RX1), and the yield curve (DGS10TO1) are all inversely correlated with the recession initiation indicator.

I thought the modified recession initiation would be a harder match, but there are quite a few correlated variables. Lets take a look at some of those in more detail

Complete list of symbols

Since it is tedious to do this one at a time, all the symbols were entered into a data frame, loaded, and aggregated together in a single xts object.

This is the complete list of symbol names and sources used in the project.